Expression Recognition Using Elastic Graph Matching

  • Yujia Cao
  • Wenming Zheng
  • Li Zhao
  • Cairong Zhou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3784)


In this paper, we proposed a facial expression recognition method based on the elastic graph matching (EGM) approach.The EGM approach is widely considered very effective due to it’s robustness against face position and lighting variations. Among all the feature extraction methods which have been used with the EGM, we choose Gabor wavelet transform according to its good performance. In order to effectively represent the facial expression information, we choose the fiducial points from the local areas where the distortion caused by expression is obvious. The better performance of the proposed method is confirmed by the JAFFE facial expression database, compared to the some previous works. We can achieve the average expression recognition rate as high as 93.4%. Moreover, we can get face recognition result simultaneously in our experiment.


Facial Expression Recognition Rate Gesture Recognition Expression Recognition Facial Expression Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yujia Cao
    • 1
    • 2
  • Wenming Zheng
    • 1
    • 2
  • Li Zhao
    • 1
    • 2
  • Cairong Zhou
    • 2
  1. 1.Research Center for Learning ScienceSoutheast UniversityNanjingChina
  2. 2.Department of Radio EngineeringSoutheast UniversityNanjingChina

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