基于视频序列的行人多目标跟踪方法研究

交通运输系统工程与信息 ›› 2007, Vol. 7 ›› Issue (4): 47-51 .

• 智能交通系统与信息技术 • 上一篇下一篇

基于视频序列的行人多目标跟踪方法研究

岳昊, 邵春福 , 赵熠 , 陈晓明

北京交通大学交通运输学院北京 100044

收稿日期:2006-12-26 修回日期:1900-01-01 出版日期:2007-08-25 发布日期:2007-08-25

A Study on Moving Pedestrian Tracking Based on Video Sequences

Yue Hao, Shao Chun-fu, Zhao Yi，Chen Xiao-ming

School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China

Received:2006-12-26 Revised:1900-01-01 Online:2007-08-25 Published:2007-08-25

摘要/Abstract

摘要： 本文研究了基于视频序列的行人多目标跟踪方法。首先利用视频图像处理技术实现背景提取、背景更新、移动目标检测。然后利用移动行人在相邻两帧图像上位置和面积的变化特点，建立匹配矩阵，完成移动目标的匹配，实现多目标跟踪；最后利用实测的视频数据检验算法，实验结果表明，该方法能清楚地绘出行人的移动轨迹，分析了跟踪轨迹中噪声产生的原因。

关键词: 视频图像处理, 跟踪算法, 多目标跟踪, 行人跟踪

Abstract: The study on tracking of moving pedestrians based on vision sequence is presented in the paper. The video sequences are processed by the background extraction and adaptation, moving objects detection, shadow detection, eroding and dilating image in order to create the moving pedestrian contour. The change of the moving pedestrian contour location and area is taken into account by the method presented here. The method first computes the centre coordinates and radius of the circle through the pedestrian contour. Secondly, the matching matrix is established by the change of the location and the radius between the different circles at two successive frames and the matching moving objects have been found. The method is tested by using the video sequences of actual measurement and the experiment results are analyzed. Under the experiment condition, the contrails of the moving pedestrians are clearly drawn with a little noise at the different image sampling interval. Finally, the application condition of the method is described.

Key words: video-based image processing, Tracking algorithm, multi-object tracking, moving pedestrian tracking

中图分类号:

TP273

岳昊, 邵春福, 赵熠, 陈晓明. 基于视频序列的行人多目标跟踪方法研究[J]. 交通运输系统工程与信息, 2007, 7(4): 47-51 .

Yue Hao, Shao Chun-fu, Zhao Yi,Chen Xiao-ming. A Study on Moving Pedestrian Tracking Based on Video Sequences[J]. Journal of Transportation Systems Engineering and Information Technology, 2007, 7(4): 47-51 .

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/abstract/abstract17551.shtml

http://www.tseit.org.cn/CN/Y2007/V7/I4/47

参考文献

1. N. J. Ferrier, S. M. Rowe, A. Blake, “Real-time traffic monitoring” Applications of Computer Vision, Proceedings of the Second IEEE Workshop on, 1994, pp.81-88.
2. 刘勃．交通流量的视频检测方法研究[博士论文]．合肥：中国科学技术大学，2005年4月。
Liu Bo. Study on the method of traffic flow detection based on vision [D]. Hefei, University of Science and Technology of China. 4, 2005.
3. 杨清夙．车辆视频检测与跟踪系统的研究与实现[硕士论文]．成都：四川大学，2004年5月。
Yang Qingsu. Research & implementation of video vehicle detection and tracking system [D]. Chengdu, Sichuan University. 5, 2004.
4. 张丽．车辆视频检测与跟踪系统的算法研究[硕士论文]．杭州：浙江大学，2003年3月。
Zhang Li. Study on the algorithm of vehicle detection and tracking system based on vision [D]. Hangzhou, Zhejiang University. 3, 2003.
5. 朱辉．视频检测技术在智能交通系统中的应用研究[硕士论文]．西安：长安大学，2002年5月。
Zhu Hui. Research of video detection technology for intelligent transportation system [D]. Xi’an, Chang’an University. 5, 2002.
6. 杨立成．高速公路视频交通监测与分析系统研究[硕士论文]．长春：吉林大学，2003年2月。
Yang Licheng. Study on the system of freeway video surveillance and analysis [D]. Changchun, Jilin University. 2, 2003.
7. Chia-Jung Pai, Hsiao-Rong Tyan, Yu-Ming Liang, Hong-Yuan Mark Liao,Sei-Wang Chen， “Pedestrian detection and tracking at crossroads”[J]. Pattern Recognition 37 (2004) 1025-1034.
8. J. Heikkilä, O. Silvén, A real-time system for monitoring of cyclists and pedestrians, IEEE Proceedings on Visual Surveillance, Fort Collins, Colorado, 1999, pp. 74–81.
9. O. Masoud, N.P. Papanikolopoulos, Robust pedestrian tracking using a model-based approach, IEEE Conference on Intelligent Transportation Systems, 1997, pp.338–343
10. H.T. Chen, H.H. Lin, T.L. Liu, Multi-object tracking using dynamical graph matching, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, Vol. 2, 2001, pp. 210–217.
11. Chunfu Shao, Yi Zhao, Hao Yue and Xu Zhang, Study on a Vision-based System for Real-time Collection of Mixed Traffic Data, Proceedings of Fifth International Conference on Traffic and Transportation Studies,Xi’an,China,2006,pp604-614.
12. Julio Cezar Silveira Jacques Jr, Cláudio Rosito Jung, Soraia Raupp Musse, Background Subtraction and Shadow Detection in Grayscale Video Sequences, Proceedings of the XVIII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI’05) 1530-1834/05, 2005.

[1]	沈振乾，苗长云，耿磊. 夜间复杂交通场景中的车辆检测和跟踪[J]. 交通运输系统工程与信息, 2016, 16(1): 46-51.
[2]	李娟,邵春福,杨励雅,李琦. 基于Kalman滤波的行人跟踪方法研究[J]. 交通运输系统工程与信息, 2009, 9(6): 148-153 .

基于视频序列的行人多目标跟踪方法研究

A Study on Moving Pedestrian Tracking Based on Video Sequences

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 2

编辑推荐

Metrics