Expression recognition using elastic graph matching

Authors:
Yujia Cao;Wenming Zheng;Li Zhao;Cairong Zhou
Affiliations:
Research Center for Learning Science, Southeast University, Nanjing, China;Research Center for Learning Science, Southeast University, Nanjing, China;Research Center for Learning Science, Southeast University, Nanjing, China;Department of Radio Engineering, Southeast University, Nanjing, China
Venue:
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Year:
2005

Citing 12
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Abstract

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.