NDLI: Non parametric motion recognition using temporal multiscale Gibbs models

Content Provider	IEEE Xplore Digital Library
Author	Fablet, R. Bouthemy, P.
Copyright Year	2001
Description	Author affiliation: IRISA, Rennes, France (Fablet, R.)
Abstract	We present an original approach for non parametric motion analysis in image sequences. It relies on the statistical modeling of distributions of local motion-related measurements computed over image sequences. Contrary to previously proposed methods, the use of temporal multiscale Gibbs models allows us to handle in a unified statistical framework both spatial and temporal aspects of motion content. The important feature of our probabilistic scheme is to make the exact computation of conditional likelihood functions feasible and simple. It enables us to straightforwardly achieve model estimation according to the ML criterion and to benefit from a statistical point of view for classification issues. We have conducted motion recognition experiments over a large set of real image sequences comprising various motion types such as temporal texture samples, human motion examples and rigid motion situations.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Pattern Analysis & Machine Intelligence
File Size	915834
File Format	PDF
ISBN	0769512720
ISSN	10636919
DOI	10.1109/CVPR.2001.990516
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image sequences Motion analysis Image motion analysis Image analysis Image sequence analysis Image recognition Computer vision Optical computing Layout Image texture analysis
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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