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Feature Selection in Audiovisual Emotion Recognition Based on Rough Set Theory

  • Yong Yang
  • Guoyin Wang
  • Peijun Chen
  • Jian Zhou
  • Kun He
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4400)

Abstract

Affective computing is becoming an important research area in intelligent computing technology. Furthermore, emotion recognition is one of the hot topics in affective computing. It is usually studied based on facial and audio information with technologies such as ANN, fuzzy set, SVM, HMM, etc. Many different facial and acoustic features are considered in emotion recognition by researchers. The question which features are important for emotion recognition is discussed in this paper. Rough set based reduction algorithms are taken as a method for feature selection in a proposed emotion recognition system. Our simulation experiment results show that rough set theory is effective in emotion recognition. Some useful features for audiovisual emotion recognition are discovered.

Keywords

Affective computing Emotion recognition Pattern recognition Rough set Feature selection 

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Yong Yang
    • 1
    • 2
  • Guoyin Wang
    • 2
  • Peijun Chen
    • 1
  • Jian Zhou
    • 1
  • Kun He
    • 2
  1. 1.School of Information Science and Technology, Southwest Jiaotong University, Chengdou, 610031P.R. China
  2. 2.Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065P.R. China

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