Fusion of local features for face recognition by multiple least square solutions

Authors:
Yuting Tao;Jian Yang
Affiliations:
Nanjing University of Science & Technology, Nanjing, China;Nanjing University of Science & Technology, Nanjing, China
Venue:
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Year:
2012

Citing 6
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Abstract

In terms of supervised face recognition, linear discriminant analysis (LDA) has been viewed as one of the most popular approaches during the past years. In this paper, taking advantage of the equivalence between LDA and the least square problem, we propose a new fusion method for face classification, based on the combination of least square solutions for local mean and local texture into multiple optimization problems. Extensive experiments on AR_Gray and Yale face database indicate the competitive performance of the proposed method, compared to the traditional LDA.