%0 Journal Article
%T Adaptive 3D Facial Feature Tracking Combining Robust Feature with Online Learning<br>综合鲁棒特征和在线学习的自适应三维人脸多特征跟踪
%A WANG Xiao-yan
%A WANG Yang-sheng
%A ZHOU Ming-cai
%A FENG Xue-tao
%A ZHOU Xiao-xu
%A <br>汪晓妍
%A 王阳生
%A 周明才
%A 冯雪涛
%A 周晓旭
%J 计算机科学
%D 2009
%I 
%X An algorithm based on robust feature combining edge strength and raw intensity and online appearance model fitting was proposed to track head pose and facial actions in video. A 3D parameterized model, CAND)DE model, was used to model the face and facial expression, a weak perspective projection method was used to model the head pose, an adaptive appearance model was built on shape free intensity and edge texture, and then a gradient decent model fitting algorithm was taken to track parameters of head pose and facial actions. Experiments demonstrate that the algorithm is more robust than using only intensity especially when the lighting condition and facial expression is complicated.
%K Visual tracking
%K Online appearance model
%K Shape free texture
%K Edge strength<br>视觉跟踪
%K 在线学习
%K 形状无关纹理
%K 边强度
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=BD80A792F7CC715053A59B25542B2EE6&yid=DE12191FBD62783C&vid=933658645952ED9F&iid=708DD6B15D2464E8&sid=002786F01A86D891&eid=1D01216AD76577EC&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=14