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Abstract:
At the present the facial expression recognition is susceptible to gender, nationality cultural factors. In order to get the robustness of face recognition method, a method based on the semantic and case-based reasoning is presented. Firstly, this method automatically extracted face low-level feature points with DVF, and extracted the wrinkles with LBP. Then based on the semantic AHP method layered facial expression, parameterize expression semantic vector. Three confidence estimators based k-NN proposed to calculate the weights of the semantic vector. Finally design facial expression classifier based on CBR. The proposed method recognized facial expression in the image high-level semantic, is robust for gender, nationality culture. The experiments are conducted on Cohn-Kande database, the whole recognition rate of 95.07% is achieved. Theoretical analysis and experimental results both show that, the proposed method has better recognition effect than others. © 2010 Binary Information Press.
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Journal of Information and Computational Science
ISSN: 1548-7741
Year: 2010
Issue: 9
Volume: 7
Page: 1868-1877
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ESI Highly Cited Papers on the List: 0 Unfold All
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30 Days PV: 0
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