Facial Expression Recognition from Image Sequences with LSVM

In order to improve the accuracy of video based facial expression recognition,we propose a local SVM based on KNN-SVM algorithm,applied in facial expression recognition．For a geometric feature test sample,we first select k nearest neighboring training samples．A local optimal SVM decision hyper-plane is rebuilt based on the similarity between the test sample and the k neighboring samples for classifying the geometric feature test sample．Four different classifiers,KNN,SVM, KNN-SVM and LSVM,were compared,and the comparison results on the Cohn-Kanade database show the effectiveness of the method．