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首页> 外文期刊>Journal of systems science & information >Framework for Freeway Auto-surveillance from Traffic Video
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Framework for Freeway Auto-surveillance from Traffic Video

机译：交通视频的高速公路自动监控框架

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摘要

Video based surveillance systems have been widely used on freeway for traffic monitoring, as the cameras can provide the most intuitionistic information. In order to manage all the traffic videos automatically, in this paper, a distributed real-time auto-surveillance system is presented. The freeway traffic videos are taken as input video from Pan Tilt Zoom (PTZ) camera, and then produces an analysis of the states and activity of the vehicles in the region of interested (ROI), if there is any abnormal instance, an alarm and corresponding traffic video are sent to awake surveillants by Ethernet. To achieve this functionality, our system relies on three main procedures. The first one initializes the system. It detects the ROI of the scene, and performs the camera calibration to remove the perspective effect of the incoming image. The second one segments moving vehicles from the images, eliminate shadow and tracks them real-time. It uses a set of methods to obtain the background of the image, extracts the moving regions and tracks these moving regions by matching them between frames of the video sequence to obtain high-level information such as color, size, velocity, and trajectories of moving vehicles. In the third procedure, activities of vehicles are analyzed based on a series of preset situations which would happen on freeway. The detail information of each vehicle and the global statistical information are checked to find out any abnormal instance, and then triggered an alarm. We present details of the system, together with experiment results which demonstrate the accuracy and time responses.
机译：由于摄像机可以提供最直观的信息，因此基于视频的监视系统已广泛用于高速公路的交通监控。为了自动管理所有交通视频，本文提出了一种分布式实时自动监控系统。高速公路交通视频被作为来自Pan Tilt Zoom（PTZ）摄像机的输入视频，然后对感兴趣区域（ROI）中车辆的状态和活动进行分析，如果有异常情况，则发出警报并相应的交通视频通过以太网发送给清醒的监视者。为了实现此功能，我们的系统依赖于三个主要过程。第一个初始化系统。它检测场景的ROI，并执行相机校准以消除传入图像的透视效果。第二部分从图像中分割出移动的车辆，消除阴影并实时跟踪它们。它使用一组方法来获取图像的背景，提取运动区域并通过在视频序列的帧之间进行匹配来跟踪这些运动区域，以获得高级信息，例如颜色，大小，速度和运动轨迹汽车。在第三步中，基于一系列可能在高速公路上发生的预设情况来分析车辆的活动。检查每辆车的详细信息和全局统计信息，以发现任何异常情况，然后触发警报。我们介绍了系统的详细信息，以及表明准确性和时间响应的实验结果。

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