%0 Journal Article
%T Improved moving objects detection method based on Gaussian mixture model<br>改进的基于高斯混合模型的运动目标检测方法
%A MA Yi-de
%A ZHU Wang-fei
%A AN Shi-xia
%A QIU Hui-yin
%A TANG Shu-sen
%A <br>马义德
%A 朱望飞
%A 安世霞
%A 邱会银
%A 汤书森
%J 计算机应用
%D 2007
%I 
%X This paper proposed an improved moving objects detection method based on Gaussian mixture model in the case of focusing on a video monitoring system with a static camera. First, for updating the parameters (mean and variance) of the Gaussian models, the learning rates of mean and variance were different: for mean, the learning rate was adaptive, while for variance, the learning rate was fixed; Second, The notion of Mean Of the Weight (MOW) was introduced, which had a big contribution for differentiating background points from foreground points. Third, Shadow was detected and removed with the help of background image. Experimental results show that the proposed method possesses better ability of learning and higher efficiency of detecting large and slow objects in busy environments.
%K motion detection
%K Gaussian mixture model
%K the learning rate
%K the mean of the weight<br>运动检测
%K 高斯混合模型
%K 学习率
%K 权值均值
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=67902007244069A8&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=F3090AE9B60B7ED1&sid=B4B54538A1E05926&eid=EEA2EB09832F05D6&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=11