Exploiting Depth Discontinuities for Vision-Based Fingerspelling Recognition
Abstract
We present a novel method for automatic fingerspelling recognition which is able to discriminate complex hand configurations with high amounts of finger occlusions. Such a scenario, while common in most fingerspelling alphabets, presents a challenge for vision methods due to the low intensity variation along important shape edges in the hand image. Our approach is based on a simple and cheap modification of the capture setup: a multi-flash camera is used with flashes strategically positioned to cast shadows along depth discontinuities in the scene, allowing efficient and accurate hand shape extraction. We then use a shift and scale invariant shape descriptor for fingerspelling recognition, demonstrating great improvement over methods that rely on features acquired by traditional edge detection and segmentation algorithms.
Cite
Text
Feris et al. "Exploiting Depth Discontinuities for Vision-Based Fingerspelling Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2004. doi:10.1109/CVPR.2004.336Markdown
[Feris et al. "Exploiting Depth Discontinuities for Vision-Based Fingerspelling Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2004.](https://mlanthology.org/cvprw/2004/feris2004cvprw-exploiting/) doi:10.1109/CVPR.2004.336BibTeX
@inproceedings{feris2004cvprw-exploiting,
title = {{Exploiting Depth Discontinuities for Vision-Based Fingerspelling Recognition}},
author = {Feris, Rogério Schmidt and Turk, Matthew and Raskar, Ramesh and Tan, Kar-Han and Ohashi, Gosuke},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2004},
pages = {155},
doi = {10.1109/CVPR.2004.336},
url = {https://mlanthology.org/cvprw/2004/feris2004cvprw-exploiting/}
}