王天旭, 周煦林, 崔丽洁, 郑江滨. 基于背景模型的车辆目标检测[J]. 微电子学与计算机, 2011, 28(7): 65-67.
引用本文: 王天旭, 周煦林, 崔丽洁, 郑江滨. 基于背景模型的车辆目标检测[J]. 微电子学与计算机, 2011, 28(7): 65-67.
WANG Tian-xu, ZHOU Xu-lin, CUI Li-jie, ZHENG Jiang-bin. The Vehicle Detection Based on Background Model[J]. Microelectronics & Computer, 2011, 28(7): 65-67.
Citation: WANG Tian-xu, ZHOU Xu-lin, CUI Li-jie, ZHENG Jiang-bin. The Vehicle Detection Based on Background Model[J]. Microelectronics & Computer, 2011, 28(7): 65-67.

基于背景模型的车辆目标检测

The Vehicle Detection Based on Background Model

  • 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.

     

    Abstract: 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.

     

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