一种新的背景模型建立及更新方法  

Novel Method for Background Modeling and Update

作　　者：戴小鹏[1] 王华伟[2] 黄璜[1] 

机构地区：[1]湖南农业大学计算机与信息工程学院,湖南长沙410128 [2]厦门大学计算机系,福建厦门361005

出　　处：《计算机应用研究》2006年第5期239-241,共3页Application Research of Computers

基　　金：国家"863"计划资助项目(863-306-ZD05);湖南农业大学人才引进基金资助项目(03YJ08)

摘　　要：提出一种新的建立背景模型和更新背景的方法。首先使用一种新颖的方法建立初始背景,然后对每一输入帧使用背景差分法获得前景,并利用分类器将前景分类为运动目标、静止目标、虚假目标、噪声,最后在背景更新阶段采用基于前景目标的背景更新方法。实验结果表明,该方法能建立可靠初始背景,并能有效地解决背景更新“死锁”问题,增强背景模型的鲁棒性。Proposes a novel background modeling and update algorithm. Firstly a novel background modeling is built and for each image sequence foreground is obtained by background subtraction, then a foreground object classifier is used to get moving object, static object, false object, and noise, finally the background model is updated by a foreground object classification based background update algorithm. Extensive experiments results on indoor and outdoor image sequences demonstrate that the proposed system can effectively build a reliable background model and resolve the deadlock problem which results from false object.

关 键 词：背景模型 前景分类 虚假目标 背景更新 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]