Abstract
In this paper, a multilinear approach based on image texture for face recognition is present. First, we extract the texture features of the facial images using the local binary pattern (LBP) algorithm. Then, we apply the high-order orthogonal iteration (HOOI) algorithm, the algebra of higher-order tensors, to obtain a compact and effective representation of the facial images based on the texture features. Our representation yields improved facial recognition rates relative to standard eigenface and tensorface especially when the facial images are confronted by a variety of viewpoints and illuminations. To evaluate the validity of our approach, a series of experiments are performed on the CMU PIE facial databases.
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