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AN EFFICIENT VIDEO-BASED VEHICLE TRAJECTORY PROCESSING APPROACH

机译:一种基于视频的有效车辆轨迹处理方法

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Vehicle trajectories provide valuable information of traffic dynamics. The paper proposed a modified video-based trajectory data processing approach to reliably and efficiently collect trajectory data on congested urban roads or at intersections. The approach is on the basis of Knoop's idea of video transformation so that traces of vehicles are visible in a single image. Different from the existing method, a mode-based background subtraction algorithm is applied in the RGB color space to alleviate the influence of a small gap. Vehicle trajectories are then directly detected by searching connected components in the segmented binary vehicle trace image. Test results show that the complete process procedure of a single lane can be finished in 1 hour for a 5-min video. Almost 97% of the trajectories can be accurately detected which is very promising.
机译:车辆轨迹提供了交通动态的有价值的信息。提出了一种改进的基于视频的轨迹数据处理方法,以可靠,有效地收集拥挤的城市道路或交叉路口的轨迹数据。该方法基于Knoop的视频转换思想,因此可以在单个图像中看到车辆的痕迹。与现有方法不同,在RGB色彩空间中应用了基于模式的背景减除算法,以减轻小间隙的影响。然后,通过在分割的二进制车辆轨迹图像中搜索连接的零部件,直接检测车辆轨迹。测试结果表明,对于5分钟的视频,单车道的完整处理过程可以在1小时内完成。可以准确地检测出将近97%的轨迹,这很有希望。

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