ML Anthology

3D Shape Context Based Gesture Analysis Integrated with Tracking Using Omni Video Array

Kohsia S. Huang, Mohan M. Trivedi
CVPRW 2005 pp. 80
doi:10.1109/CVPR.2005.382 /cvprw/2005/huang2005cvprw-3d/

Abstract

In this paper we introduce a multilayer cylindrical histogram based feature space for representing 3D shape context of human body. Dynamics of gestures are analyzed using discrete hidden Markov models (DHMM) with quantized feature vectors. Extensive experimental trials with multiple subjects and a range of gesture classes are presented. Gesture recognition accuracies of over 85% (for nine gestures, and 9 subjects) and over 95% (for seven gestures) support the basic feasibility and robustness of the approach.

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Cite

Text

Huang and Trivedi. "3D Shape Context Based Gesture Analysis Integrated with Tracking Using Omni Video Array." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2005. doi:10.1109/CVPR.2005.382

Markdown

[Huang and Trivedi. "3D Shape Context Based Gesture Analysis Integrated with Tracking Using Omni Video Array." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2005.](https://mlanthology.org/cvprw/2005/huang2005cvprw-3d/) doi:10.1109/CVPR.2005.382

BibTeX

@inproceedings{huang2005cvprw-3d,
  title     = {{3D Shape Context Based Gesture Analysis Integrated with Tracking Using Omni Video Array}},
  author    = {Huang, Kohsia S. and Trivedi, Mohan M.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2005},
  pages     = {80},
  doi       = {10.1109/CVPR.2005.382},
  url       = {https://mlanthology.org/cvprw/2005/huang2005cvprw-3d/}
}