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基于视频的交叉口目标轨迹自动采集
引用本文:杨轸,张秋晨.基于视频的交叉口目标轨迹自动采集[J].同济大学学报(自然科学版),2019,47(3):0369-0377.
作者姓名:杨轸  张秋晨
作者单位:同济大学 道路与交通工程教育部重点实验室,上海 201804,同济大学 道路与交通工程教育部重点实验室,上海 201804
基金项目:国家重点研发计划(2017YFC0803902)
摘    要:提出了一种基于视频的交叉口内目标运动轨迹自动采集方法.首先利用ViBe(Visual Background Extractor)算法提取目标前景,然后提出了基于光流的目标跟踪OPC(object-point-contour)算法,最后基于透视变换得到目标的真实轨迹和运动参数.方法可采集交叉口内所有交通对象的类别、轨迹、速度与加速度信息,并对目标停滞与遮挡现象有较好的跟踪稳定性.经检验,该方法对机动车、非机动车和行人的轨迹提取准确率分别为88.89%、86.00%和83.33%,速度提取准确率为91.71%,为交叉口管理与安全研究提供一种视频处理和数据采集手段.

关 键 词:运动轨迹  目标跟踪  视频处理  光流
收稿时间:2018/1/26 0:00:00
修稿时间:2019/1/3 0:00:00

A Video-based Framework for Automated Trajectory Collection at Intersections
YANG Zhen and ZHANG Qiuchen.A Video-based Framework for Automated Trajectory Collection at Intersections[J].Journal of Tongji University(Natural Science),2019,47(3):0369-0377.
Authors:YANG Zhen and ZHANG Qiuchen
Institution:Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China and Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Abstract:A video-based framework was presented to collect trajectories of objects at intersections. Firstly, a modified ViBe algorithm was used to extract the foreground of moving objects. Then, an OPC(Object Point Contour) matching approach was developed for paring, tracking and generating image trajectories. Finally, real world trajectories were obtained through perspective transformation so that velocity and acceleration could be estimated. The framework was stable to occlusion and stagnation. The accuracy of 88.89%, 86.00%, and 83.33% were obtained for vehicles, bicycles and pedestrians counts and 91.71% for velocity estimation. This automatic system provides a solution for data collection and video analysis for intersection safety management and research.
Keywords:trajectory  video tracking  video analysis  optical flow
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