Abstract

Color face image is composed of color information of different channels. Color image provides more information for face recognition task compared with grey scale image. A novel approach coined block diagonal non-negative matrix factorization (BDNMF) is proposed for color face representation and recognition. The approach employs block diagonal matrix to encode color information of different channels. Block diagonal constraint is imposed on the non-negative matrix factorization algorithm to factorize matrices of different channels simultaneously. And block diagonal non-negative matrix factorization algorithm is exploited to extract facial features. Nearest neighborhood classifier is adopted to identify color face samples. Experimental results on CVL and CMU PIE color face databases verify the effectiveness of the proposed approach.

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