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Dissimilarity Representations Based on Multi-Block LBP for Face Detection

  • Yoanna Martínez-Díaz
  • Heydi Méndez-Vázquez
  • Yenisel Plasencia-Calaña
  • Edel B. García-Reyes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7441)

Abstract

Face representation is one of the open problems in face detection. The recently proposed Multi-Block Local Binary Patterns (MB-LBP) representation has shown good results for this purpose. Although dissimilarity representation has proved to be effective in a variety of pattern recognition problems, to the best of our knowledge, it has never been used for face detection. In this paper, we propose new dissimilarity representations based on MB-LBP features for this task. Different experiments conducted on a public database, showed that the proposed representations are more discriminative than the original MB-LBP representation when classifying faces. Using the dissimilarity representations, a good classification accuracy is achieved even when less training data is available.

Keywords

face detection dissimilarity representation MB-LBP 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yoanna Martínez-Díaz
    • 1
  • Heydi Méndez-Vázquez
    • 1
  • Yenisel Plasencia-Calaña
    • 1
  • Edel B. García-Reyes
    • 1
  1. 1.Advanced Technologies Application CenterHavanaCuba

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