%0 Journal Article
%T Facial Expression Recognition Based on Optical Flow Techniques for Non-rigid Motion Analysis<br>基于非刚体运动光流算法的面部表情识别
%A YANG Guo-Liang
%A WANG Zhi-Liang
%A WAGN Guo-Jiang
%A CHEN Feng-Jun
%A <br>杨国亮
%A 王志良
%A 王国江
%A 陈锋军
%J 计算机科学
%D 2007
%I 
%X In this paper we address the problem of estimating the non-rigid motion in facial expression sequences. Due to the great deal Of temporal distortions that luminance patterns exhibit in facial expression images, standard optical flow algorithms are not well adapted in this context. To cope with the problem, a novel approach for estimating facial expression motion based on first-order and second-order div-curl splines constraint is presented. The numerical resolutions of this method are induced. Facial expression feature vector flows are extracted by improved optical flow algorithm and a hybrid classificer based on HMM and BP neural network is designed. The experiment results show that the performance of this approach is better than normal method.
%K Optical flow
%K Div-curl spline
%K Non-rigid motion
%K Facial expression recognition<br>光流div-curl样条
%K 非刚体运动
%K 面部表情识别
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=4500389034B4E1DAEFCB96E17649429C&yid=A732AF04DDA03BB3&vid=339D79302DF62549&iid=38B194292C032A66&sid=527AEE9F3446633A&eid=1B64850025D0BBBE&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=4