DocumentCode :
3428249
Title :
Deformable model based data compression for gesture recognition
Author :
Cheneviere, Fréedéeric ; Boukir, Samia
Author_Institution :
Univ. de La Rochelle, France
Volume :
4
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
541
Abstract :
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.
Keywords :
data compression; gesture recognition; image motion analysis; data compression; gesture recognition; motion trajectory; motion-capture system; spatio-temporal signal; Active contours; Computer vision; Data compression; Deformable models; Frequency; Humans; Principal component analysis; Shape; Spatiotemporal phenomena; Spline;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1333829
Filename :
1333829
Link To Document :
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