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Local Application of Optic Flow to Analyse Rigid versus Non-Rigid Motion
A. Lipton
ICCV Workshop on Frame-Rate Vision, September, 1999.

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Abstract

Optic flow has been a research topic of interest for many years. It has, until recently, been largely inapplicable to real-time video applications due to its computationally expensive nature. This paper presents a new, reliable flow technique called dynamic region matching, based on the work of Anandan, Lucas and Kanade, and Okutomi and Kanade, which can be combined with a motion detection algorithm (from stationary or stabilised camera image streams) to allow flow-based analyses of moving entities in real-time. If flow vectors need only be calculated for ``moving'' pixels, then the computation time is greatly reduced, making it applicable to real-time implementation on modest computational platforms (such as standard Pentium II based PCs). Applying this flow technique to moving entities provides some straightforward primitives for analysing the motion of those objects. Specifically, in this paper, methods are presented for: analysing rigidity and cyclic motion using residual flow; and determining self-occlusion and disambiguating multiple, mutually occluding entities using pixel contention.

Notes

Associated center: VASC
Associated labs/groups: People Image Analysis Consortium and Video Surveillance and Monitoring
Associated project: Video Surveillance and Monitoring

Text Reference

A. Lipton, "Local Application of Optic Flow to Analyse Rigid versus Non-Rigid Motion," ICCV Workshop on Frame-Rate Vision, September, 1999.

BibTeX Reference

@inproceedings{Lipton_1999_2934,
   author = "Alan Lipton",
   title = "Local Application of Optic Flow to Analyse Rigid versus Non-Rigid Motion",
   booktitle = "ICCV Workshop on Frame-Rate Vision",
   month = "September",
   year = "1999"
}