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Facial Expression Recognition Using Histogram Sequence of Local Gabor Gradient Code-Horizontal Diagonal and Oriented Gradient Descriptor

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Proceedings of 2017 Chinese Intelligent Systems Conference (CISC 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 460))

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Abstract

This paper present a original method for facial expression recognition, which fused with the Gabor filter and Local Gradient Code-Horizontal Diagonal (LGC-HD) as well as Histogram of Oriented Gradient (HOG). This approach firstly is used Viola-Jones algorithm to resize the facial expression image and convolve the facial expression image with Gabor filters to extract the Gabor Coefficients Maps (GCM). Then, we obtain Average Gabor Maps (AGM) by folding GCM of four orientations in each scale to reduce dimensions. The LGC-HD and HOG is applied on each AGM to obtain the LGGC-HD-HOG descriptor. At last, the Support Vector Machine (SVM) is adopted as classifier. We conclude that the method in this paper is better in recognition rate than other similar methods by analyzing the experimental result.

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Authors and Affiliations

  1. Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Huanhuan Zhang & Lin Li

Authors
  1. Huanhuan Zhang
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  2. Lin Li
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Corresponding author

Correspondence to Lin Li .

Editor information

Editors and Affiliations

  1. Beihang University , Beijing, China

    Yingmin Jia

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

    Junping Du

  3. University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

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Zhang, H., Li, L. (2018). Facial Expression Recognition Using Histogram Sequence of Local Gabor Gradient Code-Horizontal Diagonal and Oriented Gradient Descriptor. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2017 Chinese Intelligent Systems Conference. CISC 2017. Lecture Notes in Electrical Engineering, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-6499-9_24

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  • DOI: https://doi.org/10.1007/978-981-10-6499-9_24

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6498-2

  • Online ISBN: 978-981-10-6499-9

  • eBook Packages: EngineeringEngineering (R0)

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