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Elastic graph matching is one of the most well known techniques for frontal face recognition/verification and one of the few techniques that can be combined successfully with fully automatic face localization and alignment methods. In this paper, we propose an algorithm for finding the most discriminant features upon a person's face and a person-specific graph is placed in the spatial coordinates...
In this paper, two supervised methods for enhancing the classification accuracy of the Nonnegative Matrix Factorization (NMF) algorithm are presented. The idea is to extend the NMF algorithm in order to extract features that enforce not only the spatial locality, but also the separability between classes in a discriminant manner. The first method employs discriminant analysis in the features derived...
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