Face recognition by discriminant analysis with gabor tensor representation

Authors:
Zhen Lei;Rufeng Chu;Ran He;Shengcai Liao;Stan Z. Li
Affiliations:
Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Year:
2007

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Abstract

This paper proposes a novel face recognition method based on discriminant analysis with Gabor tensor representation. Although the Gabor face representation has achieved great success in face recognition, its huge number of features often brings about the problem of curse of dimensionality. In this paper, we propose a 3rd-order Gabor tensor representation derived from a complete response set of Gabor filters across pixel locations and filter types. 2D discriminant analysis is then applied to unfolded tensors to extract three discriminative subspaces. The dimension reduction is done in such a way that most useful information is retained. The subspaces are finally integrated for classification. Experimental results on FERET database show promising results of the proposed method.