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Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation based classification (SRC) has been successfully used for FR. This paper discusses the dimensionality reduction (DR) of face images under the framework of SRC. Although one important merit of SRC is that it is insensitive to...
Principal Component Analysis (PCA) is a wellknown and efficient technique for feature extraction and dimension reduction, which has been applied widely in community of machine learning and pattern recognition. But traditional PCA suffers from two disadvantages which restricts it's treatment of two dimensional data, like human faces, fingerprints, palmprints and other biological features which are...
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