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Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition

  • Anıl Yüce
  • Nuri Murat Arar
  • Jean-Philippe Thiran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8212)

Abstract

Curvature Gabor features have recently been shown to be powerful facial texture descriptors with applications on face recognition. In this paper we introduce their use in facial action unit (AU) detection within a novel framework that combines multiple Local Curvature Gabor Binary Patterns (LCGBP) on different filter sizes and curvature degrees. The proposed system uses the distances of LCGBP histograms between neutral faces and AU containing faces combined with an AU-specific feature selection and classification process. We achieve 98.6% overall accuracy in our tests with the extended Cohn-Kanade database, which is higher than achieved previously by any state-of-the-art method.

Keywords

Local Binary Pattern Facial Expression Recognition Facial Action Gabor Wavelet Active Appearance Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Anıl Yüce
    • 1
  • Nuri Murat Arar
    • 1
  • Jean-Philippe Thiran
    • 1
  1. 1.Signal Processing Laboratory (LTS5)École Polytechnique Fédérale de LausanneSwitzerland

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