ML Anthology

Real-Time Periodic Motion Detection, Analysis, and Applications

Ross Cutler, Larry S. Davis
CVPR 1999 pp. 2326-2332
doi:10.1109/CVPR.1999.784652 /cvpr/1999/cutler1999cvpr-real/

Abstract

We describe a new technique to detect and analyze periodic motion as seen from both a static and moving camera. By tracking objects of interest, we compute an object's self-similarity as it evolves in time. For periodic motion, the self-similarity measure is also periodic, and we apply time-frequency analysis to detect and characterize the periodic motion. A real-time system has been implemented to track and classify objects using periodicity. Examples of object classification, person counting, and non-stationary periodicity are provided.

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Cite

Text

Cutler and Davis. "Real-Time Periodic Motion Detection, Analysis, and Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1999. doi:10.1109/CVPR.1999.784652

Markdown

[Cutler and Davis. "Real-Time Periodic Motion Detection, Analysis, and Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1999.](https://mlanthology.org/cvpr/1999/cutler1999cvpr-real/) doi:10.1109/CVPR.1999.784652

BibTeX

@inproceedings{cutler1999cvpr-real,
  title     = {{Real-Time Periodic Motion Detection, Analysis, and Applications}},
  author    = {Cutler, Ross and Davis, Larry S.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1999},
  pages     = {2326-2332},
  doi       = {10.1109/CVPR.1999.784652},
  url       = {https://mlanthology.org/cvpr/1999/cutler1999cvpr-real/}
}