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A Method to Extract Overall Trajectory Information from Frame Sequence of Fixed Background without Object Tracking

机译:一种从无对象跟踪的固定背景帧序列中提取整个轨迹信息的方法

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In this paper, a method is proposed to extract overall motion pattern for target trajectories from RGB frame sequence in a fixed background. Compared to existing methods which perform tracing on individual targets for trajectories, proposed method extracts overall trajectory information without matching or alignment between surveillance video frames, bringing about reduction on computation cost Rather than tracking every object, researchers detect objects in each frame and record their central positions to form a 2D trajectory points cloud. A novel clustering algorithm based on the moment of inertia has been applied on the 2D point cloud to extract overall statistics trajectory information. In a traffic surveillance scenario, the proposed method provided descriptive information with efficiency, and is suitable for real-time intelligent monitoring and crowd management for future smart cities.
机译:在本文中,提出了一种方法,以提取来自固定背景中的RGB帧序列的目标轨迹的整体运动模式。与在轨迹的各个目标上执行追踪的现有方法相比,所提出的方法提取整体轨迹信息而不匹配或对调查视频帧之间的匹配或对齐,从而降低计算成本而不是跟踪每个对象,研究人员检测每个帧中的对象并记录它们的中心表格形成2D轨迹点云。基于惯性矩的新型聚类算法已经应用于2D点云以提取整体统计轨迹信息。在交通监控场景中,该方法提供了具有效率的描述性信息,适用于未来智能城市的实时智能监控和人群管理。

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