%0 Journal Article
%T A Fast Convergent Gaussian Mixture Model for Moving Object Detection<br>一种用于运动目标检测的快速收敛混合高斯模型
%A JIAO Bo
%A LI Guo-hui
%A TU Dan
%A WANG Yan-ming
%A <br>焦波
%A 李国辉
%A 涂丹
%A 汪彦明
%J 中国图象图形学报
%D 2008
%I 
%X Background model is a common method for detecting moving object in traffic surveillance video.The effect of Gaussian Mixture Model used in training background model is good,but its convergence velocity is low.At present,many improved models only accelerate the initial convergent velocity.For accelerating the convergent velocity when background changes in the process of surveillance,the models need to detect whether background has changed or not real time and then to be initialized again if background changes.In this paper we put forward a new improved Gaussian Mixture Model,which needn't be initialized again if background information changes and avoids redundant steps of detecting whether background has changed or not real time.Experiment result of the new model shows the convergent velocity in the process of surveillance is improved evidently.
%K Fast convergence
%K gaussian mixture model
%K background model
%K object detection<br>快速收敛
%K 混合高斯模型
%K 背景模型
%K 目标检测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=93530001B087EBB5E94EF9DD5E9363D3&yid=67289AFF6305E306&vid=FC0714F8D2EB605D&iid=708DD6B15D2464E8&sid=5E3A696E84245F10&eid=FCB16C6DAE3686F1&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=1&reference_num=8