Abstract
Affective computing is becoming a more and more important topic in intelligent computing technology. Emotion recognition is one of the most important topics in affective computing. It is always performed on face and voice information with such technology as ANN, fuzzy set, SVM, HMM, etc. In this paper, based on the idea of data driven data mining and rough set theory, a novel emotion recognition method is proposed. Firstly, an information system including facial features is taken as a tolerance relation in rough set, based on the idea of data driven data mining, a suitable threshold is selected for the tolerance relation. Then a reduction algorithm based on condition entropy is proposed for the tolerance relation, SVM is taken as the final classifier. Simulation experiment results show that the proposed method can use less features and get higher recognition rate, and the proposed method is proved effective and efficient.
This paper is partially supported by National Natural Science Foundation of China under Grant No.60773113 and No. 60573068, Natural Science Foundation of Chongqing under Grant CSTC2007BB2445.
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Yang, Y., Wang, G., Luo, F., Li, Z. (2008). A Data Driven Emotion Recognition Method Based on Rough Set Theory. In: Chan, CC., Grzymala-Busse, J.W., Ziarko, W.P. (eds) Rough Sets and Current Trends in Computing. RSCTC 2008. Lecture Notes in Computer Science(), vol 5306. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88425-5_47
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DOI: https://doi.org/10.1007/978-3-540-88425-5_47
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