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Transactions on Rough Sets VII pp 283–294Cite as

Feature Selection in Audiovisual Emotion Recognition Based on Rough Set Theory

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Part of the book series: Lecture Notes in Computer Science ((TRS,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.

This paper is partially supported by National Natural Science Foundation of China under Grant No.60373111, Program for New Century Excellent Talents in University (NCET), Natural Science Foundation of Chongqing under Grant No.2005BA2003, Science & Technology Research Program of Chongqing Education Commission under Grant No.040505.

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Authors and Affiliations

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdou, 610031, P.R. China

    Yong Yang, Peijun Chen & Jian Zhou

  2. Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P.R. China

    Yong Yang, Guoyin Wang & Kun He

Authors
  1. Yong Yang
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  2. Guoyin Wang
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  3. Peijun Chen
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  4. Jian Zhou
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  5. Kun He
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Editor information

James F. Peters Andrzej Skowron Victor W. Marek Ewa Orłowska Roman Słowiński Wojciech Ziarko

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© 2007 Springer Berlin Heidelberg

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Yang, Y., Wang, G., Chen, P., Zhou, J., He, K. (2007). Feature Selection in Audiovisual Emotion Recognition Based on Rough Set Theory. In: Peters, J.F., Skowron, A., Marek, V.W., Orłowska, E., Słowiński, R., Ziarko, W. (eds) Transactions on Rough Sets VII. Lecture Notes in Computer Science, vol 4400. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71663-1_18

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  • DOI: https://doi.org/10.1007/978-3-540-71663-1_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71662-4

  • Online ISBN: 978-3-540-71663-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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