| 一种有效的车辆跟踪算法与异常车辆检测 |
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| 引用本文： | 陈聪,朱煜,肖玉玲,陈宁.一种有效的车辆跟踪算法与异常车辆检测[J].医学教育探索,2015(2):205-209. |
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| 作者姓名： | 陈聪 朱煜 肖玉玲 陈宁 |
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| 作者单位： | 华东理工大学信息科学与工程学院，上海 200237,华东理工大学信息科学与工程学院，上海 200237,河南工业大学化学工业职业学院，郑州 450042,华东理工大学信息科学与工程学院，上海 200237 |
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| 基金项目： | 国家自然科学基金(61271349)；中央高校基本科研业务费专项资金(WH1214015)；河南省科技发展计划项目(142102210417)；河南省高等学校青年骨干教师资助计划项目(2013GGJS 206) |
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| 摘 要： | 交通监控视频中车辆检测、跟踪与车型判别是智能交通监控系统的重要组成部分。本文运用W4背景减除法和光流法相结合的技术进行车辆检测。利用区域滤波和空洞填充方法提高目标检测精度。采用质心距离约束和目标大小约束条件实现目标区域之间的匹配和车辆跟踪。最后，根据车辆的几何形状特征对助动车等异常车辆进行检测和标记。通过对高速公路实际视频的测试表明，本算法对机动车进行了有效的跟踪与标记，并对道路上助动车等异常车辆进行了有效的检测。
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| 关 键 词： | 背景减除法 光流法 车辆跟踪 异常车辆检测 |
| 收稿时间： | 2014/5/12 0:00:00 |
An Effective Vehicle Tracking Method and Abnormal Vehicle Detection |
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| CHEN Cong,ZHU Yu,XIAO Yu-ling and CHEN Ning.An Effective Vehicle Tracking Method and Abnormal Vehicle Detection[J].Researches in Medical Education,2015(2):205-209. |
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| Authors: | CHEN Cong ZHU Yu XIAO Yu-ling and CHEN Ning |
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| Institution: | School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China;,School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China;,Henan Vocational College of Chemical Industry, Henan University of Technology, Zhengzhou 450042, China and School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China; |
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| Abstract: | The detection and tracking of vehicle in traffic surveillance video is the important part of the intelligent transportation system. This paper proposes a vehicle detection method by combining the W4 background subtraction and optical flow method. Regional filtering and holes filling technologies are utilized to improve the accuracy of target detection. Moreover, the constraint conditions on centroid distance and target size are employed to attain the matching between target regions and the tracking of vehicles. Finally, by means of the characteristics of geometric shape, some abnormal vehicles such as motorcycles are detected and labeled. The test results on real video of highway show that the proposed algorithm can effectively track and label motor vehicle, as well as detecting abnormal vehicles such as motorcycles. |
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| Keywords: | background subtraction optical flow vehicle tracking abnormal vehicle detection |
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