%0 Journal Article
%T Object tracking using robust subspace learning in particle filter<br>基于鲁棒子空间学习的粒子滤波跟踪算法*
%A LU Wen
%A CAI Jing-ju
%A <br>陆文
%A 蔡敬菊
%J 计算机应用研究
%D 2011
%I 
%X Observing that low-dimensional linear subspaces are able to effectively model image variation caused by illumination and pose change.While most related tracking algorithms use a pre-trained view-based eigenspace representation,it is imperative to collect a large set of training images covering the range of possible appearance variation,and this representation,once learned,is not updated.This paper presented a tracking method that incrementally learned a low-dimensional subspace representation,efficiently ad...
%K object tracking
%K particle filter
%K incremental subspace learning
%K robust eigenspace learning<br>目标跟踪
%K 粒子滤波
%K 增量子空间学习
%K 鲁棒特征空间学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=49438F68A18A45243818C91105B62ABD&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=9CF7A0430CBB2DFD&sid=488E37691418A2A8&eid=153FBB08F09A16CD&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=17