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

@article{Zheng2005GAfisherAN,
  title={GA-fisher: a new LDA-based face recognition algorithm with selection of principal components},
  author={Wei-Shi Zheng and Jianhuang Lai and Pong C. Yuen},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
  year={2005},
  volume={35},
  pages={1065-1078}
}
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 dimension reduction of Sw so that it becomes nonsingular. The popular method is to select the largest nonzero eigenvalues and the corresponding… CONTINUE READING
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The use of multiple measures in taxonomic problems

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