%0 Journal Article
%T Moving Objects Detection of Adaptive Gaussian Mixture Models on HSV<br>HSV自适应混合高斯模型的运动目标检测
%A LIN Qing
%A XU Zhu
%A WANG Shi-tong
%A ZHAN Yong-zhao
%A <br>林庆
%A 徐柱
%A 王士同
%A 詹永照
%J 计算机科学
%D 2010
%I 
%X In the current computer vision apphcations,the research on extracting moving objects from video sequences is very hot. hhe traditional methods can not detect moving object in the complex environment well. Accodding to the characteristics of HSV color space, a adaptive mixed Gaussian background Modeling based on HSV color space and the way to remove the shadow was also proposed. Firstly, in order to improve the efficncicny of Modeling, an adaptive selection strategy of number of components of mixture of Gaussinas model was proposed. Secondly, according to the shadow characters in the HSV vector space,we also proposed a new method to remove the shadow of objects. The paper can also build the model quickly and remove the shadow accurately under the situation of light with big change. Compared with the traditional shadows suppression method,this method can suppress shadows to moving objects without setting the threshold value.
%K Aadaptive mixture gaussian model
%K Moving object detection
%K Shadow suppression
%K HSV<br>自适应混合高斯模型，运动目标检测，阴影消除，HSV
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=E3EBA5195E8B3E684679CDF37850E855&yid=140ECF96957D60B2&vid=42425781F0B1C26E&iid=F3090AE9B60B7ED1&sid=01622E3E475F966C&eid=BFA1E9325EA734A6&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0