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Animal gaits from video: comparative studies

Favreau Laurent, Revéret Lionel, Depraz Christine, Cani Marie-Paule
Graph. Models, 68 (2), 212–234, 2006.
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We present a method for animating 3D models of animals from existing live video sequences such as wild life documentaries. Videos are first segmented into binary images on which Principal Component Analysis (PCA) is applied. The time-varying coordinates of the images in the PCA space are then used to generate 3D animation. This is done through interpolation with Radial Basis Functions (RBF) of 3D pose examples associated with a small set of key-images extracted from the video. In addition to this processing pipeline, our main contributions are: an automatic method for selecting the best set of key-images for which the designer will need to provide 3D pose examples, and a simple algorithm based on PCA images to resolve 3D pose prediction ambiguities. These ambiguities are inherent to many animal gaits when only monocular view is available.

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BibTex References

@article{FRDC06,
author = {Laurent Favreau and Lionel Rev\'eret and Christine Depraz and Marie-Paule Cani},
title = {Animal gaits from video: comparative studies},
journal = {Graph. Models},
volume = 68,
number = {2},
pages = {212--234},
month = mar,
year = 2006
}

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