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Expression recognition from video using a coupled hidden Markov model

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3 Author(s)
Mingli Song ; Coll. of Comput. Sci., Zhejiang Univ., Hangzhou, China ; Jiajun Bu ; Chun Chen

To classify the face expressions in the video, in this paper, a system including both facial feature extraction and expression recognition is presented. The facial feature points are tracked first, then a sequence of FAP based face motion vector are deduced. These vectors are divided into two classifications, one for face expression, the other is for visual speech. Finally, a coupled hidden Markov model is trained to perform the recognition. The experimental results show that our approach is better than conventional face expression recognition system.

Published in:

TENCON 2004. 2004 IEEE Region 10 Conference  (Volume:A )

Date of Conference:

21-24 Nov. 2004