Multi-view face recognition based on tensor subspace analysis and view manifold modeling

This paper aims to address the face recognition problem with a wide variety of views. We proposed a tensor subspace analysis and view manifold modeling based multi-view face recognition algorithm by improving the TensorFace based one. Tensor subspace analysis is applied to separate the identity and view information of multi-view face images. To model the nonlinearity in view subspace, a novel view manifold is introduced to TensorFace. Thus, a uniform multi-view face model is achieved to deal with the linearity in identity subspace as well as the nonlinearity in view subspace. Meanwhile, a parameter estimation algorithm is developed to solve the view and identity factors automatically. The new face model yields improved facial recognition rates against the traditional TensorFace based method. (C) 2009 Elsevier B.V. All rights reserved.