A FUSION METHOD OF MULTIPLE FEATURES FOR CLASSIFICATION OF SMILE EXPRESSION
Jun Chen · Journal of South China Normal University · 2011
A smile expression classification system on data sets of GENKI is built which can represent real-world environments,and the support vector machine and GentleBoost algorithm are used as tools to learn.The followings are introduced: data preprocessing,Gabor features extraction,PHOG features extraction,and local binary pattern features extraction.The experiment results and detailed analysis of these results based on the GENKI dataset shows the effectiveness of the method.