NDLI: A Support Vector Machines Approach for Efficient Facial Expression Recognition

Content Provider	IEEE Xplore Digital Library
Author	Ramanathan, R. Nair, A.S. Sagar, V.V. Sriram, N. Soman, K.P.
Copyright Year	2009
Abstract	Current scenario in computer vision demands an efficient and robust technique for facial expression recognition. There is also a need for a generalized technique that can even be used for content based image retrieval and analysis. This paper introduces a novel methodology of facial expression recognition using Support Vector Machines. An efficient model is trained and developed using the necessary features extracted by employing 2D Gabor filters. Practically, six different methods for handling the feature vectors are discussed and extensively analyzed in this paper. The developed model is tested and cross validated and the detailed results are presented. It is observed that the proposed method offers a consistent and good accuracy (83.3%) for all the six basic expressions considered. In addition, the implementation complexity is reduced by minimizing the number of support vectors, unlike the traditional counterparts. The proposed method shall definitely turn out to be an effective alternative for the existing methods.
Starting Page	850
Ending Page	854
File Size	1002921
Page Count	5
File Format	PDF
ISBN	9781424451043
DOI	10.1109/ARTCom.2009.91
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-27
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Computer vision Facial expression recognition Content based retrieval Image analysis Face recognition Image retrieval Feature extraction Robustness Gabor filters Support Vector Machines Testing
Content Type	Text
Resource Type	Article

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