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Facial Expression Recognition Using Fuzzy Kernel Discriminant Analysis

  • Qingjiang Wu
  • Xiaoyan Zhou
  • Wenming Zheng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)

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.

Keywords

Facial Expression Linear Discriminant Analysis Facial Image Facial Expression Recognition Gabor Wavelet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Qingjiang Wu
    • 1
  • Xiaoyan Zhou
    • 2
    • 3
  • Wenming Zheng
    • 2
  1. 1.Department of Computer ScienceHuaqiao UniversityQuanzhouChina
  2. 2.Research Center for Learning ScienceSoutheast UniversityNanjingChina
  3. 3.Department of Electrics EngineeringNanjing University of Information Science and TechnologyNanjingChina

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