%0 Journal Article
%T Fast dynamic Gaussian mean-shift algorithm based on adaptive bandwidth<br>基于自适应带宽的快速动态高斯核均值漂移算法
%A ZHOU Fang-fang
%A FAN Xiao-ping
%A YE Zhen
%A <br>周芳芳
%A 樊晓平
%A 叶 榛
%J 控制理论与应用
%D 2008
%I 
%X The Gaussian kernel mean-shift algorithm which is deduced from kernel density estimation has not been widely employed in applications because of its low convergence rate.We propose a dynamic mean-shift algorithm based on adaptive bandwidth.The number of data sets is reduced by adaptive space discretization;the convergence rate is improved by dynamically updating the data set,and the efficiency is promoted by replacing the overlapping points with a special point in the iterations.The anisotropic bandwidth is updated according to the diameter of the data set.Experiments validate the improvement of the convergence rate of Gaussian mean-shift with lower complexity in computation.
%K mean shift
%K Gaussian kernel
%K kernel density estimation
%K adaptive bandwidth<br>均值漂移
%K 高斯核
%K 核密度估计
%K 自适应带宽
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=B22AC4CA71A88A3A7F7E53837A50ED2A&yid=67289AFF6305E306&vid=C5154311167311FE&iid=E158A972A605785F&sid=C7B13290323C226E&eid=EF9E84B2DA79FF23&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=8