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An ICA-Based Other-Race Effect Elimination for Facial Expression Recognition

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Biometric Recognition (CCBR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10996))

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Abstract

Other-race effect affects the performance of multi-race facial expression recognition significantly. Though this phenomenon has been noticed by psychologists and computer vision researchers for decades, few work has been done to eliminate this influence caused by other-race effect. This work proposes an ICA-based other-race effect elimination method for 3D facial expression recognition. Firstly, the local depth features are extracted from 3D face point clouds, and then independent component analysis is used to project the features into a subspace in which the feature components are mutually independent. Second, a mutual information based feature selection method is adopted to determine race-sensitive features. Finally, the features after race-sensitive information elimination are utilized to conduct facial expression recognition. The proposed method is evaluated on BU-3DFE database, and the results reveal that the proposed method is effective to other-race effect elimination and could improve the multi-race facial expression recognition performance.

This work is supported by National Natural Science Foundation of China (Grant No.61672132), Science and Technology Foundation of Liaoning Province of China (Grant No.20170520234), CERNET next generation Internet technical innovation project (Grant No. NGII20170419 and Grant No. NGII20170631).

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Author information

Authors and Affiliations

  1. Dalian Key Lab of Digital Technology for National Culture, College of Computer Science and Engineering, Dalian Minzu University, Dalian, 116600, Liaoning, China

    Mingliang Xue & Xiaodong Duan

  2. Department of Computing, Curtin University, Kent Street, Perth, WA, 6102, Australia

    Wanquan Liu

  3. School of Electronic Information Engineering, North China University of Technology, Beijing, 100144, China

    Yuehai Wang

Authors
  1. Mingliang Xue
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  2. Xiaodong Duan
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  3. Wanquan Liu
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  4. Yuehai Wang
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Corresponding author

Correspondence to Xiaodong Duan .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Zhou

  2. Beihang University, Beijing, China

    Yunhong Wang

  3. Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Xinjiang University, Urumqi, China

    Zhenhong Jia

  5. Tsinghua University, Beijing, China

    Jianjiang Feng

  6. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  7. Xinjiang University, Urumqi, China

    Kurban Ubul

  8. Tsinghua University, Shenzhen, China

    Zhenhua Guo

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Xue, M., Duan, X., Liu, W., Wang, Y. (2018). An ICA-Based Other-Race Effect Elimination for Facial Expression Recognition. In: Zhou, J., et al. Biometric Recognition. CCBR 2018. Lecture Notes in Computer Science(), vol 10996. Springer, Cham. https://doi.org/10.1007/978-3-319-97909-0_40

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  • DOI: https://doi.org/10.1007/978-3-319-97909-0_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97908-3

  • Online ISBN: 978-3-319-97909-0

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