DocumentCode :
383346
Title :
Two-hand gesture recognition using coupled switching linear model
Author :
Kuno, Yoshinori ; Shimada, N.
Volume :
1
fYear :
2002
fDate :
2002
Firstpage :
9
Abstract :
We present a method of coupling multiple switching linear models. The coupled switching linear model is an interactive process of two switching linear models. Coupling is given through causal influence between their hidden discrete states. The parameters of this model are learned via EM algorithm. Tracking is performed through the coupled-forward algorithm based on Kalman filtering and a collapsing method. A model with maximum likelihood is selected out of a few learned models during tracking. We demonstrate the application of the proposed model to tracking and recognizing two-hand gestures.
Keywords :
Kalman filters; computer vision; gesture recognition; maximum likelihood estimation; probability; tracking; Coupled backward algorithm; EM algorithm; Kalman filtering; coupling multiple switching linear models; maximum likelihood estimation; model specification; probability density; tracking; two-hand gesture recognition; Active shape model; Ear; Equations; Hidden Markov models; Man machine systems; Mechanical systems; Shape control; Spline; Tracking; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-1695-X
Type :
conf
DOI :
10.1109/ICPR.2002.1044576
Filename :
1044576
Link To Document :
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