ML Anthology

Gesture Recognition: Focus on the Hands

Pradyumna Narayana, Ross Beveridge, Bruce A. Draper
CVPR 2018
doi:10.1109/CVPR.2018.00549 /cvpr/2018/narayana2018cvpr-gesture/

Abstract

Gestures are a common form of human communication and important for human computer interfaces (HCI). Recent approaches to gesture recognition use deep learning methods, including multi-channel methods. We show that when spatial channels are focused on the hands, gesture recognition improves significantly, particularly when the channels are fused using a sparse network. Using this technique, we improve performance on the ChaLearn IsoGD dataset from a previous best of 67.71% to 82.07%, and on the NVIDIA dataset from 83.8% to 91.28%.

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Cite

Text

Narayana et al. "Gesture Recognition: Focus on the Hands." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018. doi:10.1109/CVPR.2018.00549

Markdown

[Narayana et al. "Gesture Recognition: Focus on the Hands." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.](https://mlanthology.org/cvpr/2018/narayana2018cvpr-gesture/) doi:10.1109/CVPR.2018.00549

BibTeX

@inproceedings{narayana2018cvpr-gesture,
  title     = {{Gesture Recognition: Focus on the Hands}},
  author    = {Narayana, Pradyumna and Beveridge, Ross and Draper, Bruce A.},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2018},
  doi       = {10.1109/CVPR.2018.00549},
  url       = {https://mlanthology.org/cvpr/2018/narayana2018cvpr-gesture/}
}