智能系统学报2008，Vol.3Issue(5)：455-466,12.
基于局部SVM分类器的表情识别方法
Facial expression recognition based on local SVM classifiers
摘要
Abstract
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.关键词
人脸表情识别/局部支撑向量机/活动形状模型/几何特征Key words
facial expression recognition/local SVM/active shape model/geometry feature分类
信息技术与安全科学引用本文复制引用
孙正兴,徐文晖..基于局部SVM分类器的表情识别方法[J].智能系统学报,2008,3(5):455-466,12.基金项目
National High Technology Research and Development Program (863) of China (2007AA01Z334) （863）
National Natural Science Foundation of China (69903006, 60373065, 0721002) （69903006, 60373065, 0721002）
New Century Excellent Talents in University (NCET-04-0460). （NCET-04-0460）
