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This paper illustrates that elaborately selecting some discriminative patches instead of using all patches is helpful for recognition tasks. We propose an effective method called bagging greedy algorithm (BGA) for choosing a collection of patches that is discriminative in terms of classification. Compared with greedy algorithm, BGA is less likely to get into local optimum. Based on the subset of patches,...
A novelty method of face recognition combined with the fusion of local 2DGabor mean values and 2DPCA dimension deduction based on subspace analysis is proposed. Firstly, each facial image in the training sample set is divided according to the five special face regions and then the features of five key regions are extracted through 2DGabor wavelet, mean values are calculated from feature vectors gained...
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