NDLI: Gabor feature representation method based on block statistics and its application to facial expression recognition

Content Provider	IEEE Xplore Digital Library
Author	Shuaishi Liu Yantao Tian Chuan Wan
Copyright Year	2010
Description	Author affiliation: School of Communication Engineering, Jilin University, Changchun, China (Shuaishi Liu; Yantao Tian; Chuan Wan)
Abstract	Facial expression representation based on Gabor features has attracted more and more attention and achieved great success in facial expression recognition for some favorable attributes of Gabor wavelets such as spatial locality and orientation selectivity. A large number of Gabor features are produced with varying parameters in the position, scale and orientation of filters, which cause huge computational complexity. In some existing methods, useful discriminatory information may be lost due to down sampling Gabor features directly. To reduce the loss, a Gabor features representation method based on block statistics is proposed in this paper. In addition, Support Vector Machine is used to match the features. The effect of this method is demonstrated by template matching test on JAFFE database, and the comparative test results show that this method can yield better recognition accuracy with much fewer Gabor features as well as less CPU time of feature matching.
Starting Page	6267
Ending Page	6271
File Size	1108819
Page Count	5
File Format	PDF
ISBN	9781424467129
e-ISBN	9781424467129
DOI	10.1109/WCICA.2010.5554379
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face recognition Feature extraction Gabor filters Support vector machines Face Lighting Erbium Support vector machine Facial expression recognition Gabor feature Block statistics
Content Type	Text
Resource Type	Article

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