NDLI: Facial Complex Expression Recognition Based on Fuzzy Kernel Clustering and Support Vector Machines

Content Provider	IEEE Xplore Digital Library
Author	Hui Zhao Zhiliang Wang Jihui Men
Copyright Year	2007
Description	Author affiliation: Xinjiang Univ., Beijing (Hui Zhao)
Abstract	Present methods of facial expression recognition usually designate an expression image as one kind of six facial basic expressions. However, a facial expression usually is a complex expression that consists of several basic expressions. This paper proposes a facial complex expression recognition algorithm based on fuzzy kernel clustering and support vector machines. This algorithm designs the binary facial complex expression classification tree by using fuzzy kernel clustering algorithm, trains support vector machines at each node of the binary classification tree and describes the complexity of a facial expression according as the result of support vector machines classification. Experimental results indicate that the proposed algorithm generates higher accuracy for the JAFFE database and achieves better performance than 1-a-r SVMs. In addition, experimental results show that the result of the proposed method is more accord with practice than the result of traditional expression recognition methods.
Starting Page	562
Ending Page	566
File Size	260628
Page Count	5
File Format	PDF
ISBN	9780769528755
DOI	10.1109/ICNC.2007.372
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Design engineering Image recognition Face recognition Clustering algorithms Support vector machine classification Humans Facial animation Kernel Classification tree analysis
Content Type	Text
Resource Type	Article

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