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Generic versus Salient Region-Based Partitioning for Local Appearance Face Recognition

  • Hazım Kemal Ekenel
  • Rainer Stiefelhagen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

In this paper, we investigate different partitioning schemes for local appearance-based face recognition. Five different salient region-based partitioning approaches are analyzed and they are compared to a generic partitioning scheme. Extensive experiments have been conducted on the AR, CMU PIE, FRGC, Yale B, and Extend Yale B face databases. The experimental results show that generic partitioning provides better performance than salient region-based partitioning schemes.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Hazım Kemal Ekenel
    • 1
  • Rainer Stiefelhagen
    • 1
  1. 1.Computer Science DepatmentUniversität Karlsruhe (TH)KarlsruheGermany

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