Post-processing on LDA's discriminant vectors for facial feature extraction

Authors:
Kuanquan Wang;Wangmeng Zuo;David Zhang
Affiliations:
Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;Biometrics Research Centre, Department of Computing, The Hong Kong Polytechnic University, Hong Kong
Venue:
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Year:
2005

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Abstract

Linear discriminant analysis (LDA) based methods have been very successful in face recognition. Recently, pre-processing approaches have been used to further improve recognition performance but few investigations have been made into the use of post-processing techniques. This paper intends to explore the feasibility and efficiency of the post-processing technique on LDA's discriminant vectors. In this paper we propose a Gaussian filtering approach to post-process the discriminant vectors. The results of our experiments demonstrate that, post-processing technique can be used to improve recognition performance.