%0 Journal Article
%T Improvement on adaptive mixture Gaussian background model<br>自适应混合高斯背景模型的改进
%A LI Quan-min
%A ZHANG Yun-chu
%A <br>李全民
%A 张运楚
%J 计算机应用
%D 2007
%I 
%X To improve the quality of motion segmentation, the background reconstruction and foreground mergence time control mechanism were incorporated into the adaptive mixture Gaussian background model. The background reconstruction algorithm constructed a static background image from a video sequence which contained moving objects in the scene, and then the static background image was used to initialize the background model. The foreground mergence time control mechanism was introduced to make the foreground mergence time adjustable and independent of the model's learning rate. The experimental results prove the effectiveness of the algorithm.
%K video surveillance
%K motion segmentation
%K mixture Gaussian background model
%K background reconstruction<br>视觉监控
%K 运动分割
%K 混合高斯背景模型
%K 背景重构
%K 自适应
%K 混合高斯
%K 背景模型
%K 改进
%K background
%K model
%K Gaussian
%K mixture
%K adaptive
%K 有效性
%K 重构算法
%K 结果
%K 实验
%K 持续时间
%K 调节
%K 学习速率
%K 控制机制
%K 初始化
%K 背景图像
%K 视频序列
%K 动态场景
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD27430512E4A682E6D9BD9B55&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=5D311CA918CA9A03&sid=9EAD63ADE6B277ED&eid=FA004A8A4ED1540B&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=10