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)

Abstract

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 L2 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.

Keywords

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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