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Detection and Recognition of Periodic, Nonrigid Motion (1997)
| Venue: | INTERNATIONAL JOURNAL OF COMPUTER VISION |
| Citations: | 96 - 0 self |
BibTeX
@ARTICLE{Polana97detectionand,
author = {Ramprasad Polana and Randal C. Nelson},
title = {Detection and Recognition of Periodic, Nonrigid Motion},
journal = {INTERNATIONAL JOURNAL OF COMPUTER VISION},
year = {1997},
volume = {23},
pages = {261--282}
}
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Abstract
The recognition of nonrigid motion, particularly that arising from human movement (and by extension from the locomotory activity of animals) has typically made use of high-level parametric models representing the various body parts (legs, arms, trunk, head etc.) and their connections to each other. Such model-based recognition has been successful in some cases; however, the methods are often difficult to apply to real-world scenes, and are severely limited in their generalizability. The first problem arises from the difficulty of acquiring and tracking the requisite model parts, usually specific joints such as knees, elbows or ankles. This generally requires some prior high-level understanding and segmentation of the scene, or initialization by a human operator. The second problem, with generalization, is due to the fact that the human model is not much good for dogs or birds, and for each new type of motion, a new model must be hand-crafted. In this paper, we show that the recognition...
Keyphrases
nonrigid motion specific joint locomotory activity human model new type high-level parametric model human movement much good various body part real-world scene new model requisite model part human operator prior high-level understanding model-based recognition first problem arises second problem
