Expression Recognition Based on Twice Feature Selection and Support Vector Machines
Hui Zhao · Computer Knowledge and Technology · 2008
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.