Robust Face Recognition by Group Sparse Representation That Uses Samples from List of Subjects

  • Dimche Kostadinov
  • Sviatoslav Voloshynovskiy
  • Sohrab Ferdowsi
  • Maurits Diephuis
  • Rafał Scherer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8468)


In this paper we consider group sparsity for robust face recognition. We propose a model for inducing group sparsity with no constraints on the definition of the structure of the group, coupled with locality constrained regularization. We formulate the problem as bounded distance regularized L 2 norm minimization with group sparsity inducing, non-convex constrains. We apply convex relaxation and a branch and bound strategy to find an approximation to the original problem. The empirical results confirm that with this approach of deploying a very simple non-overlapping group structure we outperform several state-of-the-art sparse coding based image classification methods.


Face recognition sparse representation group sparsity 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Dimche Kostadinov
    • 1
  • Sviatoslav Voloshynovskiy
    • 1
  • Sohrab Ferdowsi
    • 1
  • Maurits Diephuis
    • 1
  • Rafał Scherer
    • 2
  1. 1.Computer Science DepartmentUniversity of GenevaGenevaSwitzerland
  2. 2.Institute of Computational IntelligenceCzȩstochowa University of TechnologyCzȩstochowaPoland

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