Facial expression recognition based on local SVM classifiers
Wenhui Xu · Caai Transactions on Intelligent Systems · 2008
This paper presents a novel technique developed for the identification of facial expressions in video sources.The method uses two steps: facial expression feature extraction and expression classification.First we used an active shape model(ASM) based on a facial point tracking system to extract the geometric features of facial expressions in videos.Then a new type of local support vector machine(LSVM) was created to classify the facial expressions.Four different classifiers using KNN,SVM,KNN-SVM,and LSVM were compared with the new LSVM.The results on the Cohn-Kanade database showed the effectiveness of our method.