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Analysis and monitoring of a high density traffic flow at T-intersection using statistical computer vision based approach

机译:基于统计计算机视觉的方法对T形交叉口的高密度交通流进行分析和监控

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A reliable traffic flow monitoring and traffic analysis approach using computer vision techniques has been proposed in this paper. The exponential increase in traffic density at urban intersections in the past few decades has raised precious and challenging demands to computer vision algorithms and technological solutions. The focus of this paper is to suggest a statistical based approach to determine the traffic parameters at heavily crowded urban intersections. The algorithm in addition to accurate tracking and counting of freeway traffic also offers high efficiency for determining vehicle count at a high traffic density T-intersection. The system uses Intel Open CV library for image processing. The implementation of algorithm is done using C++. The real time video sequence is obtained from a stationary camera placed atop a high building overlooking the particular T intersection. This paper suggests a dynamic method where each vehicle at a T intersection is passed through a number of detection zones and the final count of vehicles is derived from a statistical equation.
机译:本文提出了一种使用计算机视觉技术的可靠交通流量监控和交通分析方法。在过去的几十年中,城市交叉路口的交通密度呈指数级增长,这对计算机视觉算法和技术解决方案提出了宝贵而具有挑战性的要求。本文的重点是提出一种基于统计的方法来确定拥挤的城市交叉路口的交通参数。该算法除了可以准确跟踪和统计高速公路交通流量外,还可以在高交通密度T型交叉路口提供高效的车辆数量确定功能。系统使用Intel Open CV库进行图像处理。算法的实现是使用C ++完成的。实时视频序列是从放置在俯瞰特定T路口的高层建筑上方的固定摄像机获得的。本文提出了一种动态方法,其中T交叉口的每辆车都要经过多个检测区域,然后从统计方程中得出最终的车辆数量。

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