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In this paper, the method of kernel Fisher discriminant (KFD) is analyzed and its nature is revealed, i.e., KFD is equivalent to kernel principal component analysis (KPCA) plus Fisher linear discriminant analysis (LDA). Based on this result, a more transparent KFD algorithm is proposed. That is, KPCA is first performed and then LDA is used for a second feature extraction in the KPCA-transformed space...
In this paper, a Complex LDA based combined Fisherfaces framework, coined Complex Fisherfaces, is developed for face feature extraction and recognition. In this framework, Principal Component Analysis (PCA) and Kernel PCA (KPCA) are first used for feature extraction. Then, the resulting PCA-based linear features and KPCA-based nonlinear features are integrated by complex vectors and, Complex LDA is...
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