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Feature Fusion of Gradient Direction and LBP for Facial Expression Recognition

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Biometric Recognition (CCBR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9428))

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Abstract

Feature extraction is an important step in facial expression recognition. A novel method is proposed based on feature fusion which combines gradient direction and LBP features. Firstly, eyes are located through the integration projection method. And the operation of image rotating, cropping and normalizing is conducted based on eyes’ position. Secondly, the image is partitioned into nine non-overlapping regions with different weight, then the gradient direction and LBP features are extracted and fused. The fused features generated from each of the regions are concatenated to form the feature vector which represents the facial expression. Finally, K-nearest neighbor algorithm is performed for classification. Experiments on JAFFE and Cohn-Kanade facial expression databases show that the proposed method achieves better performance for facial expression recognition.

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Author information

Authors and Affiliations

  1. Tianjin Key Lab for Advanced Signal and Image Processing, Civil Aviation University of China, Tianjin, China

    Yu Li & Liang Zhang

Authors
  1. Yu Li
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  2. Liang Zhang
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Corresponding author

Correspondence to Yu Li .

Editor information

Editors and Affiliations

  1. Civil Aviation University of China, Tianjin, China

    Jinfeng Yang

  2. and Technology, Tianjin Institute of Science, Tianjin, China

    Jucheng Yang

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  5. Sun Yat-sen University, Guangzhou, China

    Weishi Zheng

  6. Tsinghua University, Beijing, China

    Jianjiang Feng

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© 2015 Springer International Publishing Switzerland

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Li, Y., Zhang, L. (2015). Feature Fusion of Gradient Direction and LBP for Facial Expression Recognition. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds) Biometric Recognition. CCBR 2015. Lecture Notes in Computer Science(), vol 9428. Springer, Cham. https://doi.org/10.1007/978-3-319-25417-3_50

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  • DOI: https://doi.org/10.1007/978-3-319-25417-3_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25416-6

  • Online ISBN: 978-3-319-25417-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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