CCBR 2015: Biometric Recognition pp 416-422 | Cite as

Facial Expression Recognition Based on Gabor Feature and SRC

  • Xiaojun Lu
  • Lingmei Kong
  • Mengzhu Liu
  • Xiangde Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9428)

Abstract

We present a facial expression recognition algorithm in this paper, which is based on a combination of the Gabor Feature and the Sprase Representation based Classification(SRC). First, improved Gabor filter is used to extract features. Then we use Principle Component Analysis (PCA) to reduce the dimension of Gabor feature to avoid redundancy. Finally, SRC is used to recognize and classify facial expression. Experiments on facial expression database JAFFE and Cohn-Kanade show that our approach is effective for both dimension reduction and recognition performance. The proposed method achieve 97.68% recognition accuracy on JAFFE.

Keywords

Facial expression recognition Gabor feature Principle Component Analysis(PCA) Sparse Representation based Classification(SRC) 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Xiaojun Lu
    • 1
  • Lingmei Kong
    • 1
  • Mengzhu Liu
    • 1
  • Xiangde Zhang
    • 1
  1. 1.School of SciencesNortheastern UniversityShenyangChina

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