ML Anthology

Automatic Recognition of Fingerspelled Words in British Sign Language

Stephan Liwicki, Mark Everingham
CVPRW 2009 pp. 50-57
doi:10.1109/CVPRW.2009.5204291 /cvprw/2009/liwicki2009cvprw-automatic/

Abstract

We investigate the problem of recognizing words from video, fingerspelled using the British Sign Language (BSL) fingerspelling alphabet. This is a challenging task since the BSL alphabet involves both hands occluding each other, and contains signs which are ambiguous from the observer's viewpoint. The main contributions of our work include: (i) recognition based on hand shape alone, not requiring motion cues; (ii) robust visual features for hand shape recognition; (iii) scalability to large lexicon recognition with no re-training. We report results on a dataset of 1,000 low quality webcam videos of 100 words. The proposed method achieves a word recognition accuracy of 98.9%.

PDF CVPRW Semantic Scholar

Cite

Text

Liwicki and Everingham. "Automatic Recognition of Fingerspelled Words in British Sign Language." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2009. doi:10.1109/CVPRW.2009.5204291

Markdown

[Liwicki and Everingham. "Automatic Recognition of Fingerspelled Words in British Sign Language." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2009.](https://mlanthology.org/cvprw/2009/liwicki2009cvprw-automatic/) doi:10.1109/CVPRW.2009.5204291

BibTeX

@inproceedings{liwicki2009cvprw-automatic,
  title     = {{Automatic Recognition of Fingerspelled Words in British Sign Language}},
  author    = {Liwicki, Stephan and Everingham, Mark},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2009},
  pages     = {50-57},
  doi       = {10.1109/CVPRW.2009.5204291},
  url       = {https://mlanthology.org/cvprw/2009/liwicki2009cvprw-automatic/}
}