基于背景模型的车辆目标检测  

The Vehicle Detection Based on Background Model

作　　者：王天旭[1] 周煦林[2] 崔丽洁[1] 郑江滨[1] 

机构地区：[1]西北工业大学计算机学院,陕西西安710129 [2]西安微电子技术研究所,陕西西安710065

出　　处：《微电子学与计算机》2011年第7期65-67,共3页Microelectronics & Computer

基　　金：国家自然科学基金项目(60970069);航天创新基金项目(2007);西北工业大学研究生创业种子基金(Z2010069)

摘　　要：为了实现对交通车辆快速准确地统计,文中提出一种自适应权值的背景更新方法以适应道路环境的复杂变化.首先在多个通道建立单高斯背景统计模型,然后利用场景中像素的概率分布实现对运动区域的准确检测,最后根据检测结果实现对交通流量的统计.实验结果表明:该方法能够对运动车辆进行快速准确地检测和统计,并对场景的光照变化等影响具有较高的鲁棒性.To calculate vehicle flow fast and accurately,a self-adapting weight method is proposed to update the background model to fit the complex changes in the traffic scene.The single Gaussian models are established in multi-channels for foreground extraction,and the probability distribution of pixels in the traffic scene is utilized to detect the moving region.After above operations,the traffic flow is calculated by the result of detection finally.The proposed method is not only to detect moving vehicles and calculate traffic flow effectively but also is robust to illumination changes,which is demonstrated in our experiment.

关 键 词：交通流量统计 单高斯模型 自适应权值 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]