Abstract
Facial expression recognition is becoming more and more important in computer application, such as health care, children education, etc. Based on geometric feature and appearance feature, there are a few works have been done on facial expression recognition using such methods as ANN, SVM, etc. In this paper, considering geometric feature only, a novel approach based on rough set theory and SVM is proposed. The experiment results show this approach can get high recognition ratio and reduce the cost of calculation.
This paper is partially supported by National Natural Science Foundation of China under Grant No.60373111 and 60573068, 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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© 2006 Springer-Verlag Berlin Heidelberg
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Chen, P., Wang, G., Yang, Y., Zhou, J. (2006). Facial Expression Recognition Based on Rough Set Theory and SVM. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_112
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DOI: https://doi.org/10.1007/11795131_112
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36297-5
Online ISBN: 978-3-540-36299-9
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