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Facial Expression Recognition Based on Subregion Weighted Fusion and LDA

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Communications, Signal Processing, and Systems (CSPS 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 571))

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Abstract

The facial expression recognition occupies an increasingly important position. In this paper, the static emoticon images are analyzed, and the geometrical priori based weighting strategy is used for feature fusion. The disadvantages of the preliminary features extracted by the traditional methods lack the discriminant characteristics. An improved Linear Discriminant Analysis (LDA) algorithm based on intraclass divergence matrix correction is proposed. The data is sent to the Generalized Regression Neural Network (GRNN) classifier for identification and has achieved good results.

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References

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Author information

Authors and Affiliations

  1. Information Science and Technology College, Dalian Maritime University, Dalian, 116026, Liaoning, China

    Hui Lin, Yan Wang, Zhenzhen Wang, Mengli Sun, Shiqiang Zhang, Xiaofei Shi & Xiaokai Liu

Authors
  1. Hui Lin
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  2. Yan Wang
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  3. Zhenzhen Wang
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  4. Mengli Sun
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  5. Shiqiang Zhang
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  6. Xiaofei Shi
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  7. Xiaokai Liu
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Corresponding author

Correspondence to Yan Wang .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  3. School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China

    Xin Liu

  4. School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, China

    Zhenyu Na

  5. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China

    Min Jia

  6. College of Physical and Electronic Information, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Cite this paper

Lin, H. et al. (2020). Facial Expression Recognition Based on Subregion Weighted Fusion and LDA. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_302

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  • DOI: https://doi.org/10.1007/978-981-13-9409-6_302

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9408-9

  • Online ISBN: 978-981-13-9409-6

  • eBook Packages: EngineeringEngineering (R0)

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