Face recognition by inverse fisher discriminant features

Authors:
Xiao-Sheng Zhuang;Dao-Qing Dai;P. C. Yuen
Affiliations:
Center for Computer Vision and Department of Mathematics, Sun Yat-Sen(Zhongshan)University, Guangzhou, China;Center for Computer Vision and Department of Mathematics, Sun Yat-Sen(Zhongshan)University, Guangzhou, China;Department of Computer Science, Hong Kong Baptist University, Hong Kong
Venue:
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Year:
2006

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Abstract

For face recognition task the PCA plus LDA technique is a famous two-phrase framework to deal with high dimensional space and singular cases. In this paper, we examine the theory of this framework: (1) LDA can still fail even after PCA procedure. (2) Some small principal components that might be essential for classification are thrown away after PCA step. (3) The null space of the within-class scatter matrix Swcontains discriminative information for classification. To eliminate these deficiencies of the PCA plus LDA method we thus develop a new framework by introducing an inverse Fisher criterion and adding a constrain in PCA procedure so that the singularity phenomenon will not occur. Experiment results suggest that this new approach works well.