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Facial Expression Recognition Based on Quaternion-Space and Multi-features Fusion

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Rough Sets and Knowledge Technology (RSKT 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9436))

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Abstract

There is an increasing trend of using feature fusion technique in facial expression recognition. However, when traditional serial or parallel feature fusion methods are used, the problem of highly dimensional features and insufficient fusion of possible feature categories always exist. In order to solve these problems, a novel facial expression recognition method based on quaternion-space and multi-features fusion is proposed. Firstly, four different kinds of expression features are extracted such as Gabor wavelet, LBP, LPQ and DCT features, then PCA+CCA framework is proposed and used to reduce the dimensions of the four original features. Secondly, quaternion is used to construct the combinative features. Thirdly, a novel quaternion-space HDA method is proposed and used as the dimensional reduction method of the combinative features. Finally, SVM is used and set as the classifier. Experimental results indicate that the proposed method is capable of fusing four kinds of features more effectively while it achieves higher recognition rates than the traditional feature fusion methods.

This paper is partially supported by The National Natural Science Foundation of China under Grant No.61472056 and No.61300059, and the Ministry of Science, ICT & Future Planning(MSIP) of Korea in the ICT R & D Program 2013 under Grant No.10039149.

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Authors and Affiliations

  1. Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, People’s Republic of China

    Yong Yang, Shubo Cai & Qinghua Zhang

  2. School of Information and Communication Engineering, Inha University, Incheon, 402-751, Korea

    Yong Yang

Authors
  1. Yong Yang
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  2. Shubo Cai
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  3. Qinghua Zhang
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Corresponding author

Correspondence to Yong Yang .

Editor information

Editors and Affiliations

  1. University of Milano-Bicocca, Milano, Italy

    Davide Ciucci

  2. Chongqing University of Posts and Telecommunications, Chongqing, China

    Guoyin Wang

  3. Indian Statistical Institute, Kolkata, India

    Sushmita Mitra

  4. Zhejiang Ocean University, Zhejiang, China

    Wei-Zhi Wu

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Yang, Y., Cai, S., Zhang, Q. (2015). Facial Expression Recognition Based on Quaternion-Space and Multi-features Fusion. In: Ciucci, D., Wang, G., Mitra, S., Wu, WZ. (eds) Rough Sets and Knowledge Technology. RSKT 2015. Lecture Notes in Computer Science(), vol 9436. Springer, Cham. https://doi.org/10.1007/978-3-319-25754-9_46

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  • DOI: https://doi.org/10.1007/978-3-319-25754-9_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25753-2

  • Online ISBN: 978-3-319-25754-9

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