摘要
本文提出了一种基于背景相减法和对称差分法来进行运动目标检测的方法。首先通过混和高斯模型建立运动区域的背景模型,并对背景进行实时的更新,然后通过背景相减法确定运动目标区域,再和对称差分法相结合,得到比较可靠的运动目标区域。
A novel moving object detection based on adaptive background subtraction and symmetrical differencing is presented in this paper. Firstly, a background model is based on adaptive mixture Gauss model, and update the background real-timely, then we gain the moving object region using background subtraction, and then ,we combined the background subtraction with symmetrical differencing to gain more reliable moving object region. The result of the experiment demonstrates that the algorithm runs quickly and veraciously.
出处
《微计算机信息》
北大核心
2007年第25期99-101,共3页
Control & Automation
关键词
运动目标检测
高斯模型
减背景法
对称差分
moving object detection, Gauss model, background subtraction ,symmetrical differencing.