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Camera calibration for the surround-view system: a benchmark and dataset (2312.16499v1)

Published 27 Dec 2023 in cs.CV

Abstract: Surround-view system (SVS) is widely used in the Advanced Driver Assistance System (ADAS). SVS uses four fisheye lenses to monitor real-time scenes around the vehicle. However, accurate intrinsic and extrinsic parameter estimation is required for the proper functioning of the system. At present, the intrinsic calibration can be pipeline by utilizing checkerboard algorithm, while extrinsic calibration is still immature. Therefore, we proposed a specific calibration pipeline to estimate extrinsic parameters robustly. This scheme takes a driving sequence of four cameras as input. It firstly utilizes lane line to roughly estimate each camera pose. Considering the environmental condition differences in each camera, we separately select strategies from two methods to accurately estimate the extrinsic parameters. To achieve accurate estimates for both front and rear camera, we proposed a method that mutually iterating line detection and pose estimation. As for bilateral camera, we iteratively adjust the camera pose and position by minimizing texture and edge error between ground projections of adjacent cameras. After estimating the extrinsic parameters, the surround-view image can be synthesized by homography-based transformation. The proposed pipeline can robustly estimate the four SVS camera extrinsic parameters in real driving environments. In addition, to evaluate the proposed scheme, we build a surround-view fisheye dataset, which contains 40 videos with 32,000 frames, acquired from different real traffic scenarios. All the frames in each video are manually labeled with lane annotation, with its GT extrinsic parameters. Moreover, this surround-view dataset could be used by other researchers to evaluate their performance. The dataset will be available soon.

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References (30)
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[2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Chen, Y., Zhang, L., Shen, Y., Zhao, B.N., Zhou, Y.: Extrinsic self-calibration of the surround-view system: A weakly supervised approach. IEEE Transactions on Multimedia., 1–1 (2022) https://doi.org/10.1109/TMM.2022.3144889 Chen et al. [2023] Chen, Y., Xiang, Z., Du, W.: Improving lane detection with adaptive homography prediction. The Visual Computer. 39(2), 581–595 (2023) Li et al. [2022] Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Qiao, Y., Dai, J.: Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX., pp. 1–18 (2022) Ma et al. [2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Chen, Y., Xiang, Z., Du, W.: Improving lane detection with adaptive homography prediction. The Visual Computer. 39(2), 581–595 (2023) Li et al. [2022] Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Qiao, Y., Dai, J.: Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX., pp. 1–18 (2022) Ma et al. [2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Qiao, Y., Dai, J.: Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX., pp. 1–18 (2022) Ma et al. [2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. 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In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  2. Chen, Y., Zhang, L., Shen, Y., Zhao, B.N., Zhou, Y.: Extrinsic self-calibration of the surround-view system: A weakly supervised approach. IEEE Transactions on Multimedia., 1–1 (2022) https://doi.org/10.1109/TMM.2022.3144889 Chen et al. [2023] Chen, Y., Xiang, Z., Du, W.: Improving lane detection with adaptive homography prediction. The Visual Computer. 39(2), 581–595 (2023) Li et al. [2022] Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Qiao, Y., Dai, J.: Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX., pp. 1–18 (2022) Ma et al. [2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Chen, Y., Xiang, Z., Du, W.: Improving lane detection with adaptive homography prediction. The Visual Computer. 39(2), 581–595 (2023) Li et al. [2022] Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Qiao, Y., Dai, J.: Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX., pp. 1–18 (2022) Ma et al. [2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Qiao, Y., Dai, J.: Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX., pp. 1–18 (2022) Ma et al. [2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. 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The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. 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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. 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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. 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[2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Qiao, Y., Dai, J.: Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX., pp. 1–18 (2022) Ma et al. [2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  4. Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Qiao, Y., Dai, J.: Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX., pp. 1–18 (2022) Ma et al. [2021] Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. 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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. 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Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  5. Ma, Y., Liu, Y., Zhang, L., Cao, Y., Guo, S., Li, H.: Research review on parking space detection method. Symmetry. 13(1), 128 (2021) Ma and Xie [2010] Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. 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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ma, C., Xie, M.: A method for lane detection based on color clustering. In: 2010 Third International Conference on Knowledge Discovery and Data Mining., pp. 200–203 (2010) Wang et al. [2014] Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Wang, J., Mei, T., Kong, B., Wei., H.: An approach of lane detection based on inverse perspective mapping. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)., pp. 35–38 (2014). https://doi.org/10.1109/ITSC.2014.6957662 Maya and Tharini [2020] Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. 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In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. 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[2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. 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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. 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[2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Maya, P., Tharini, C.: Performance analysis of lane detection algorithm using partial hough transform. In: Maya, P and Tharini, C., pp. 1–4 (2020) Punagin and Punagin [2020] Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. 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In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. 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[2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. 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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. 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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. 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[2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. 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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. 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In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. 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Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Punagin, A., Punagin, S.: Analysis of lane detection techniques on structured roads using opencv. International Journal for Research in Applied Science and Engineering Technology. 8, 2994–3003 (2020) Teo et al. [2021] Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Teo, T.Y., Sutopo, R., Lim, J.M.-Y., Wong, K.: Innovative lane detection method to increase the accuracy of lane departure warning system. Multimedia Tools and Applications. 80, 2063–2080 (2021) Haris et al. [2023] Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. 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The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. 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In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. 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In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. 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In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. 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In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. 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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. 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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. 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[2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. 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In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Haris, M., Hou, J., Wang, X.: Lane line detection and departure estimation in a complex environment by using an asymmetric kernel convolution algorithm. The Visual Computer. 39(2), 519–538 (2023) Huval et al. [2015] Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. 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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. 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Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Cheng-Yue, R., Mujica, F., Coates, A.: An empirical evaluation of deep learning on highway driving. Computer Science. (2015) Lee et al. [2017] Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. 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In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. 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In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.-H., Hong, H.S., Han, S.-H., Kweon, I.S.: Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. In: IEEE International Conference on Computer Vision (ICCV)., pp. 1947–1955 (2017). https://doi.org/10.1109/ICCV.2017.215 Pan et al. [2018] Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. 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[2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. 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[2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Pan, X., Shi, J., Luo, P., Wang, X., Tang, X.: Spatial as deep: Spatial cnn for traffic scene understanding. arXiv e-prints. (2018) Hou et al. [2019] Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. 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[2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Loy, C.C.: Learning lightweight lane detection cnns by self attention distillation. In: IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1013–1021 (2019). https://doi.org/10.1109/ICCV.2019.00110 Hou et al. [2020] Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. 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In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. [2021] Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. 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[2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. 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In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hou, Y., Ma, Z., Liu, C., Hui, T.-W., Loy, C.C.: Inter-region affinity distillation for road marking segmentation. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12483–12492 (2020). https://doi.org/10.1109/CVPR42600.2020.01250 Tabelini et al. 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[2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. 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In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Tabelini, L., Berriel, R., Paixao, T.M., Badue, C., De Souza, A.F., Oliveira-Santos, T.: Polylanenet: Lane estimation via deep polynomial regression. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 6150–6156 (2021) Qin et al. [2020] Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. 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In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. 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Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. 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[2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. 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In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Qin, Z., Wang, H., Li, X.: Ultra fast structure-aware deep lane detection. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16, pp. 276–291 (2020) Hedi and Lončarić [2012] Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Hedi, A., Lončarić, S.: A system for vehicle surround view. IFAC Proceedings Volumes. 45(22), 120–125 (2012) Natroshvili and Scholl [2017] Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Natroshvili, K., Scholl, K.-U.: Automatic extrinsic calibration methods for surround view systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 82–88 (2017) Ueshiba and Tomita [2002] Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Ueshiba, T., Tomita, F.: Calibration of multi-camera systems using planar patterns. Sensors. 8, 4 (2002) Zhao et al. [2014] Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhao, K., Iurgel, U., Meuter, M., Pauli, J.: An automatic online camera calibration system for vehicular applications. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1490–1492 (2014) Choi et al. [2018] Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. 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In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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[2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. 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[2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. 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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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[2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. 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In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  23. Choi, K., Jung, H.G., Suhr, J.K.: Automatic calibration of an around view monitor system exploiting lane markings. Sensors. 18(8), 2956 (2018) Liu et al. [2019] Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  24. Liu, X., Zhang, L., Shen, Y., Zhang, S., Zhao, S.: Online camera pose optimization for the surround-view system. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 383–391 (2019) Zhang et al. [2020] Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  25. Zhang, T., Zhang, L., Shen, Y., Ma, Y., Zhao, S., Zhou, Y.: Oecs: Towards online extrinsics correction for the surround-view system. In: 2020 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2020) Zhang et al. [2021] Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  26. Zhang, T., Zhao, N., Shen, Y., Shao, X., Zhang, L., Zhou, Y.: Roecs: A robust semi-direct pipeline towards online extrinsics correction of the surround-view system. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 3153–3161 (2021) Lourakis [2010] Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  27. Lourakis, M.I.: Sparse non-linear least squares optimization for geometric vision. In: Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part II 11, pp. 43–56 (2010) Moré [2006] Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  28. Moré, J.J.: The levenberg-marquardt algorithm: implementation and theory. In: Numerical Analysis: Proceedings of the Biennial Conference Held at Dundee, June 28–July 1, 1977, pp. 105–116 (2006) Dubská and Herout [2013] Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  29. Dubská, M., Herout, A.: Real projective plane mapping for detection of orthogonal vanishing points. In: BMVC (2013) Yogamani et al. [2019] Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019) Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
  30. Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Varley, P., O’Dea, D., Uricár, M., Milz, S., Simon, M., Amende, K., others.: Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9308–9318 (2019)
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