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View Invariants for Human Action Recognition

Vasu Parameswaran, Rama Chellappa
CVPR 2003 pp. 613-619
doi:10.1109/CVPR.2003.1211523 /cvpr/2003/parameswaran2003cvpr-view/

Abstract

This paper presents two approaches for the representation and recognition of human action in video, aiming for view-point invariance. The paper first presents new results using a 2D approach presented earlier. Inherent limitations of the 2D approach are discussed and a new 3D approach that builds on recent work on 3D model-based invariants, is presented. Each action is represented as a unique curve in a 3D invariance space, surrounded by an acceptance volume ('action volume'). Given a video sequence, 2D quantities from the image are calculated and matched against candidate action volumes in a probabilistic framework. The theory is presented followed by results on arbitrary projections of motion-capture data which demonstrate a high degree of tolerance to viewpoint change.

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Text

Parameswaran and Chellappa. "View Invariants for Human Action Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2003. doi:10.1109/CVPR.2003.1211523

Markdown

[Parameswaran and Chellappa. "View Invariants for Human Action Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2003.](https://mlanthology.org/cvpr/2003/parameswaran2003cvpr-view/) doi:10.1109/CVPR.2003.1211523

BibTeX

@inproceedings{parameswaran2003cvpr-view,
  title     = {{View Invariants for Human Action Recognition}},
  author    = {Parameswaran, Vasu and Chellappa, Rama},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2003},
  pages     = {613-619},
  doi       = {10.1109/CVPR.2003.1211523},
  url       = {https://mlanthology.org/cvpr/2003/parameswaran2003cvpr-view/}
}