GA-fisher: a new LDA-based face recognition algorithm with selection of principal components

Abstract

This paper addresses the dimension reduction problem in Fisherface for face recognition. When the number of training samples is less than the image dimension (total number of pixels), the within-class scatter matrix (Sw) in linear discriminant analysis (LDA) is singular, and principal component analysis (PCA) is suggested to employ in Fisherface for… (More)
DOI: 10.1109/TSMCB.2005.850175

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@article{Zheng2005GAfisherAN, title={GA-fisher: a new LDA-based face recognition algorithm with selection of principal components}, author={Wei-Shi Zheng and Jian-Huang Lai and Pong C. Yuen}, journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)}, year={2005}, volume={35}, pages={1065-1078} }