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Facial Expression Recognition Based on Adaptive Weighted Fusion Histograms

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Intelligent Computing Theories and Technology (ICIC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7996))

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Abstract

In order to improve the performance of expression recognition, this paper proposes a facial expression recognition method based on adaptive weighted fusion histograms. Firstly, the method obtains expression sub-regions by pretreatment, and calculates the contribution maps (CM) of each expression sub-region. Secondly, this method extracts Histograms of Oriented Gradient by the Kirsch operator and extracts histograms of intensity by centralized binary pattern (CBP), then the paper fuses the Histograms by parallel manner and the fused histograms are weighted by CMs. At last, the weighted fused histograms are used to classify by the Euclidean Distance and the nearest neighbor method. Experimental results which are obtained by applying the proposed algorithm and the Gabor wavelet, LBP, LBP+LPP, Local Gabor and AAM on JAFFE face expression dataset show that the proposed method achieves better performance for the face expression recognition.

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Author information

Authors and Affiliations

  1. College of Computer and Information, Hefei University of Technology, China

    Min Hu, Yanxia Xu, Liangfeng Xu & Xiaohua Wang

  2. Affective Computing and Advanced Intelligent Machines AnHui Key Laboratory, Hefei, 230009, China

    Min Hu, Yanxia Xu & Xiaohua Wang

Authors
  1. Min Hu
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  2. Yanxia Xu
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  3. Liangfeng Xu
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  4. Xiaohua Wang
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Editor information

Editors and Affiliations

  1. Machine Learning and Systems Biology Laboratory, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Electrical Engineering, University of Ulsan, 680-749 #7-413, San 29, Muger Dong, Ulsan, South Korea

    Kang-Hyun Jo

  3. Guangxi University for Nationalities, 530006, Nanning, Guangxi, China

    Yong-Quan Zhou

  4. School of Computer Science and Engineering, Inha University, 402-751, Incheon, South Korea

    Kyungsook Han

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© 2013 Springer-Verlag Berlin Heidelberg

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Hu, M., Xu, Y., Xu, L., Wang, X. (2013). Facial Expression Recognition Based on Adaptive Weighted Fusion Histograms. In: Huang, DS., Jo, KH., Zhou, YQ., Han, K. (eds) Intelligent Computing Theories and Technology. ICIC 2013. Lecture Notes in Computer Science(), vol 7996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39482-9_54

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  • DOI: https://doi.org/10.1007/978-3-642-39482-9_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39481-2

  • Online ISBN: 978-3-642-39482-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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