Face Recognition in Uncontrolled Conditions Using Sparse Representation and Local Features

  • Alessandro Adamo
  • Giuliano Grossi
  • Raffaella Lanzarotti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)

Abstract

Face recognition in presence of either occlusions, illumination changes or large expression variations is still an open problem. This paper addresses this issue presenting a new local-based face recognition system that combines weak classifiers yielding a strong one. The method relies on sparse approximation using dictionaries built on a pool of local features extracted from automatically cropped images. Experiments on the AR database show the effectiveness of our method, which outperforms current state-of-the art techniques.

Keywords

Sparse representation face recognition face partial occlusions expression variations illumination variations local features 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alessandro Adamo
    • 1
  • Giuliano Grossi
    • 2
  • Raffaella Lanzarotti
    • 2
  1. 1.Dipartimento di MatematicaUniversità degli Studi di MilanoMilanoItaly
  2. 2.Dipartimento di InformaticaUniversità degli Studi di MilanoMilanoItaly

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