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

  • Authors:
  • Xinbo Gao;Chunna Tian

  • Affiliations:
  • School of Electronic Engineering, Xidian University, Xi'an 710071, China;School of Electronic Engineering, Xidian University, Xi'an 710071, China

  • Venue:
  • Neurocomputing
  • Year:
  • 2009

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Abstract

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.