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SEMD Based Sparse Gabor Representation for Eyeglasses-Face Recognition

  • Caifang Song
  • Baocai Yin
  • Yanfeng Sun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6754)

Abstract

Sparse representation for face recognition has been exploited in past years. Several sparse representation algorithms have been developed. In this paper, a novel eyeglasses-face recognition approach, SEMD Based Sparse Gabor Representation, is proposed. Firstly, for a robust representation to misalignment, a sparse Gabor representation is proposed. Secondly, spatially constrained earth mover’s distance is employed instead of Euclidean distance to measure the similarity between original data and reconstructed data. The proposed algorithm for eyeglasses-face recognition has been evaluated under different eyeglasses-face databases. The experimental results reveal that the proposed approach is validity and has better recognition performance than that obtained using other traditional methods.

Keywords

Eyeglasses-face recognition Sparse Gabor Representation Spatially EMD Virtual sample library 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Caifang Song
    • 1
  • Baocai Yin
    • 1
  • Yanfeng Sun
    • 1
  1. 1.Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and TechnologyBeijing University of TechnologyBeijingChina

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