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17th International Conference on Pattern Recognition (ICPR'04) - Volume 4
Deformable Model based Data Compression for Gesture Recognition
Cambridge UK
August 23-August 26
ISBN: 0-7695-2128-2
Fr?d?ric Chenevi?re, Universit? de La Rochelle, France
Samia Boukir, Universit? de La Rochelle, France
We aim at recognizing a set of dance gestures from contemporary ballet. Our input data are motion trajectories followed by the joints of a dancing body provided by a motion-capture system. It is obvious that direct use of the original signals is unreliable and expensive. Therefore, we propose a suitable tool for nonuniform sub-sampling of spatio-temporal signals. The key of our approach is the use of a deformable model to provide a compact and efficient representation of motion trajectories.
Citation:
Fr?d?ric Chenevi?re, Samia Boukir, "Deformable Model based Data Compression for Gesture Recognition," icpr, vol. 4, pp.541-544, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 4, 2004
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