Bukva: Russian Sign Language Alphabet
Abstract: This paper investigates the recognition of the Russian fingerspelling alphabet, also known as the Russian Sign Language (RSL) dactyl. Dactyl is a component of sign languages where distinct hand movements represent individual letters of a written language. This method is used to spell words without specific signs, such as proper nouns or technical terms. The alphabet learning simulator is an essential isolated dactyl recognition application. There is a notable issue of data shortage in isolated dactyl recognition: existing Russian dactyl datasets lack subject heterogeneity, contain insufficient samples, or cover only static signs. We provide Bukva, the first full-fledged open-source video dataset for RSL dactyl recognition. It contains 3,757 videos with more than 101 samples for each RSL alphabet sign, including dynamic ones. We utilized crowdsourcing platforms to increase the subject's heterogeneity, resulting in the participation of 155 deaf and hard-of-hearing experts in the dataset creation. We use a TSM (Temporal Shift Module) block to handle static and dynamic signs effectively, achieving 83.6% top-1 accuracy with a real-time inference with CPU only. The dataset, demo code, and pre-trained models are publicly available.
- Facilitating the communication with deaf people: Building a largest saudi sign language dataset. Journal of King Saud University - Computer and Information Sciences, 35(8):101642, 2023.
- A new 2d static hand gesture colour image dataset for asl gestures. 2011.
- Exploring collection of sign language videos through crowdsourcing. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2):1–24, 2022.
- Modeling image variability in appearance-based gesture recognition. In ECCV Workshop on Statistical Methods in Multi-Image and Video Processing, pages 7–18, 2006.
- M. Grif and Y. Kondratenko. Development of a software module for recognizing the fingerspelling of the russian sign language based on lstm. Journal of Physics: Conference Series, (1), Oct. 2021.
- Deep residual learning for image recognition, 2015.
- Recognition of jsl finger spelling using convolutional neural networks. In 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA), pages 85–88, 2017.
- Real-time sign language fingerspelling recognition using convolutional neural networks from depth map. 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), pages 136–140, 2015.
- Slovo: Russian sign language dataset. In Computer Vision Systems: 14th International Conference, ICVS 2023, Vienna, Austria, September 27–29, 2023, Proceedings, page 63–73, 2023.
- Hagrid – hand gesture recognition image dataset. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pages 4572–4581, January 2024.
- A comparison of convolutional neural networks for kazakh sign language recognition. Eastern-European Journal of Enterprise Technologies, pages 44–54, 10 2021.
- Lexicon-free fingerspelling recognition from video: Data, models, and signer adaptation. Comput. Speech Lang., 46:209–232, 2016.
- M. Kuprashevich and I. Tolstykh. Mivolo: Multi-input transformer for age and gender estimation, 07 2023.
- Tsm: Temporal shift module for efficient video understanding, 2019.
- I. Loshchilov and F. Hutter. Sgdr: Stochastic gradient descent with warm restarts, 2017.
- Russian sign language dactyl recognition. In 2019 42nd International Conference on Telecommunications and Signal Processing (TSP), pages 726–729, 2019.
- Bangla sign language alphabet recognition using transfer learning based convolutional neural network. The Bangladesh journal of scientific research, 31-33:20–26, 2020.
- Mobilenetv2: Inverted residuals and linear bottlenecks, 2019.
- Fingerspelling recognition in the wild with iterative visual attention. 2019 IEEE/CVF International Conference on Computer Vision (ICCV), pages 5399–5408, 2019.
- American sign language fingerspelling recognition in the wild. 2018 IEEE Spoken Language Technology Workshop (SLT), pages 145–152, 2018.
- Karsl: Arabic sign language database. 2021.
- Nsl23 dataset for alphabets of nepali sign language, 2023.
- E. Szyszka. Polish Sign Language Alphabet 100, 2021.
- Mobileone: An improved one millisecond mobile backbone, 2023.
- Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
- Mediapipe hands: On-device real-time hand tracking. ArXiv, abs/2006.10214, 2020.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.