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《Computer Knowledge and Technology》 2008-36
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Expression Recognition Based on Twice Feature Selection and Support Vector Machines

LI Gui-lin1,ZHAO Hui1,2(1.Institute of Information and Scientific Engineering,Xinjiang University,Urumqi 830046,China;2.University of Science and Technology Beijing,Beijing 100083,China)  
To describe an expression recognition algrithm aims at reducing the training volume and enhancing the validity of features.It employed the sort PCA and LDA to get the optimal expression vector,and used FKC to reduce effective dataset again and build binary de-cision tree to train SVM.Experimental results in the JAFFE database indicate that the proposed algorithm generates higher accuracy than others and shorten the training time simultaneity.
【CateGory Index】: TP391.41
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