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Continuous Emotion Recognition Using Gabor Energy Filters

  • Mohamed Dahmane
  • Jean Meunier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6975)

Abstract

Automatic facial expression analysis systems try to build a mapping between the continuous emotion space and a set of discrete expression categories (e.g. happiness, sadness). In this paper, we present a method to recognize emotions in terms of latent dimensions (e.g. arousal, valence, power). The method we applied uses Gabor energy texture descriptors to model the facial appearance deformations, and a multiclass SVM as base learner of emotions. To deal with more naturalistic behavior, the SEMAINE database of naturalistic dialogues was used.

Keywords

Support Vector Machine Emotion Recognition Local Binary Pattern Gesture Recognition Baseline Method 
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-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mohamed Dahmane
    • 1
  • Jean Meunier
    • 1
  1. 1.CP 6128, Succursale Centre-VilleDIRO, University of MontrealMontrealCanada

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