警察的眼睛:真实世界的自动检测交通违规

Ramesh Marikhu, J. Moonrinta, M. Ekpanyapong, M. Dailey, S. Siddhichai
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引用次数: 13

摘要

危险变道、违章超车、错道行驶在道路交通事故中所占的比例很高,仅次于超速事故。自动交通应用通常包括移动车辆的检测和分割作为一个关键的过程。背景减法和阴影检测是动态环境中前景斑点分割中最具挑战性的任务。处理来自多个摄像机的连续高分辨率图像需要在精度和速度之间取得有效的平衡。“警察之眼”是我们开发的移动实时交通监控系统,可自动检测交通违规行为。警察的眼睛对警察执行交通法规是有用的,即使在没有警察的情况下,也会增加对交通法规的遵守。该系统利用图像处理和高效的计算机视觉技术对从IP摄像机获取的图像序列进行检测,以检测非法越过实线。自动实线交叉检测系统可用于交通违例率极高的地方,以及众所周知会造成交通拥堵和本可避免的事故的地方。该系统可以安装在路堤、十字路口、车道变化限制区域、禁止停车区域或任何观察到司机故意违反交通法规的地方。我们已经将该系统安装在工业级嵌入式PC中,并将其部署在警察模型中。现场经验评估结果表明,该系统在各种现实交通场景中表现良好。
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Police Eyes: Real world automated detection of traffic violations
Dangerous lane changing, illegal overtaking, and driving in the wrong lane account for a high percentage of the total accidents that occur on the road, second only to accidents due to over-speeding. Automated traffic applications typically encompass the detection and segmentation of moving vehicles as a crucial process. Background subtraction and shadow detection are amongst the most challenging tasks involved in the segmentation of foreground blobs in dynamic environments. An effective balance between accuracy and speed is required to process a continuous feed of high resolution images from multiple cameras. Police Eyes is a mobile, real-time traffic surveillance system we have developed to enable automatic detection of traffic violations. Police Eyes would be useful to police for enforcing traffic laws and would also increase compliance with traffic laws even in the absence of police. The system detects illegal crossings of solid lines using image processing and efficient computer vision techniques on image sequences acquired from IP cameras. The automatic solid line crossing detection system can be used at locations where the traffic violations are notoriously high and are known to create traffic congestion and avoidable accidents. The system can be installed on an embankment, at an intersection area, at a lane change restriction area, at a no parking area or anywhere there is an observed pattern of drivers intentionally violating traffic laws. We have installed the system in an industrial grade embedded PC and deployed it in a police mannequin. Results of an empirical field evaluation show that the system performs well in a variety of real-world traffic scenes.
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