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Facial Expression Recognition Using Fuzzy Kernel Discriminant Analysis

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Fuzzy Systems and Knowledge Discovery (FSKD 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4223))

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Abstract

In this paper, we address the facial expression recognition task using fuzzy kernel discriminant analysis (Fuzzy KDA) method. The Fuzzy KDA method improves the performance of kernel discriminant analysis (KDA) by considering the class membership of each training sample. We conduct the facial expression recognition on two well-known facial expression databases to demonstrate the better performance of the proposed method.

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© 2006 Springer-Verlag Berlin Heidelberg

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Wu, Q., Zhou, X., Zheng, W. (2006). Facial Expression Recognition Using Fuzzy Kernel Discriminant Analysis. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_96

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  • DOI: https://doi.org/10.1007/11881599_96

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45916-3

  • Online ISBN: 978-3-540-45917-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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