Impact of Design Decisions in Scanpath Modeling (2405.08981v1)
Abstract: Modeling visual saliency in graphical user interfaces (GUIs) allows to understand how people perceive GUI designs and what elements attract their attention. One aspect that is often overlooked is the fact that computational models depend on a series of design parameters that are not straightforward to decide. We systematically analyze how different design parameters affect scanpath evaluation metrics using a state-of-the-art computational model (DeepGaze++). We particularly focus on three design parameters: input image size, inhibition-of-return decay, and masking radius. We show that even small variations of these design parameters have a noticeable impact on standard evaluation metrics such as DTW or Eyenalysis. These effects also occur in other scanpath models, such as UMSS and ScanGAN, and in other datasets such as MASSVIS. Taken together, our results put forward the impact of design decisions for predicting users' viewing behavior on GUIs.
- A comparison of scanpath comparison methods. Behavior research methods 47 (2015), 1377–1392.
- PathGAN: Visual scanpath prediction with generative adversarial networks. In Proceedings of the European Conference on Computer Vision (ECCV) Workshops. 0–0.
- Wentao Bao and Zhenzhong Chen. 2020. Human scanpath prediction based on deep convolutional saccadic model. Neurocomputing 404 (2020), 154–164.
- Donald J Berndt and James Clifford. 1994. Using dynamic time warping to find patterns in time series. In Proceedings of the 3rd international conference on knowledge discovery and data mining. 359–370.
- Beyond Memorability: Visualization Recognition and Recall. IEEE Transactions on Visualization and Computer Graphics 22, 1 (2016).
- Predicting human scanpaths in visual question answering. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 10876–10885.
- Zhenzhong Chen and Wanjie Sun. 2018. Scanpath Prediction for Visual Attention using IOR-ROI LSTM.. In IJCAI. 642–648.
- Aladine Chetouani and Leida Li. 2020. On the use of a scanpath predictor and convolutional neural network for blind image quality assessment. Signal Processing: Image Communication 89 (2020), 115963.
- SAM: Pushing the limits of saliency prediction models. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 1890–1892.
- Predicting artificial visual field losses: A gaze-based inference study. Journal of Vision 19, 14 (2019), 22–22.
- Scanpathnet: A recurrent mixture density network for scanpath prediction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 5010–5020.
- Eye tracking scanpath analysis on web pages: how many users?. In Proceedings of the ninth biennial ACM symposium on eye tracking research & applications. 103–110.
- Ramin Fahimi. 2018. Sequential selection, saliency and scanpaths. (2018).
- Ramin Fahimi and Neil DB Bruce. 2021. On metrics for measuring scanpath similarity. Behavior Research Methods 53 (2021), 609–628.
- Predicting visual importance across graphic design types. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. 249–260.
- A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on pattern analysis and machine intelligence 20, 11 (1998), 1254–1259.
- UEyes: Understanding Visual Saliency across User Interface Types. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. 1–21.
- Raymond M Klein. 2000. Inhibition of return. Trends in cognitive sciences 4, 4 (2000), 138–147.
- Matthias Kümmerer and Matthias Bethge. 2021. State-of-the-art in human scanpath prediction. arXiv preprint arXiv:2102.12239 (2021).
- DeepGaze III: Modeling free-viewing human scanpaths with deep learning. Journal of Vision 22, 5 (2022), 7–7.
- Daniël Lakens. 2013. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front. Psychol. 4, 863 (2013).
- Understanding Visual Saliency in Mobile User Interfaces. In Proceedings of the Intl. Conf. on Human-computer interaction with mobile devices and services (MobileHCI).
- Scanpath Prediction in Panoramic Videos via Expected Code Length Minimization. arXiv preprint arXiv:2305.02536 (2023).
- Learning a convolutional neural network for image compact-resolution. IEEE Transactions on Image Processing 28, 3 (2018), 1092–1107.
- ScanGAN360: A generative model of realistic scanpaths for 360 images. IEEE Transactions on Visualization and Computer Graphics 28, 5 (2022), 2003–2013.
- A simple way to estimate similarity between pairs of eye movement sequences. Journal of Eye Movement Research 5, 1 (2012), 1–15.
- Meinard Müller. 2007. Dynamic time warping. Information retrieval for music and motion (2007), 69–84.
- Thuyen Ngo and BS Manjunath. 2017. Saccade gaze prediction using a recurrent neural network. In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 3435–3439.
- On aliased resizing and surprising subtleties in GAN evaluation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 11410–11420.
- Components of visual orienting. Attention and performance X: Control of language processes 32 (1984), 531–556.
- ScanDMM: A Deep Markov Model of Scanpath Prediction for 360° Images. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 6989–6999.
- Visual scanpath prediction using IOR-ROI recurrent mixture density network. IEEE transactions on pattern analysis and machine intelligence 43, 6 (2019), 2101–2118.
- A review & analysis of mindfulness research in HCI: Framing current lines of research and future opportunities. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. 1–13.
- An Improved Dynamic Time Warping Method Combining Distance Density Clustering for Eye Movement Analysis. Journal of Mechanics in Medicine and Biology 23, 02 (2023), 2350031.
- Scanpath prediction on information visualisations. IEEE Transactions on Visualization and Computer Graphics (2023).
- Active fixation control to predict saccade sequences. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3184–3193.
- Predicting human saccadic scanpaths based on iterative representation learning. IEEE Transactions on Image Processing 28, 7 (2019), 3502–3515.
- UIED: a hybrid tool for GUI element detection. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. 1655–1659.
- Review of visual saliency prediction: Development process from neurobiological basis to deep models. Applied Sciences 12, 1 (2021), 309.
- Predicting the visual saliency of the people with VIMS. In 2019 IEEE Visual Communications and Image Processing (VCIP). IEEE, 1–4.
- The prediction of saliency map for head and eye movements in 360 degree images. IEEE Transactions on Multimedia 22, 9 (2019), 2331–2344.
- Viewing behavior supported visual saliency predictor for 360 degree videos. IEEE Transactions on Circuits and Systems for Video Technology 32, 7 (2021), 4188–4201.