Kalman filtering used in video-based traffic monitoring system

被引:5
|
作者
Qiu, Zhijun
Yao, Danya
机构
[1] Univ Wisconsin, Dept Civil & Environm Engn, Madison, WI 53706 USA
[2] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
关键词
Kalman filtering; spatial filtering; position matching; corner detection;
D O I
10.1080/15472450500455211
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Video object tracking is an important method of traffic detection in Intelligent Transportation Systems. In video traffic tracking systems the matching method is often used to find the position of moving objects. In this article an improved algorithm of corner feature extraction is presented and corner points are tracked as the feature points of traffic objects. The tracking precision is mainly decided by matching algorithms. If the matching is not accurate, good tracking results cannot be achieved. In this article Kalman Filtering is used to track the moving traffic objects. In this system two kinds of data are used: One is from the general matching algorithm, which is the representation of the target's position; the other is detected by a spatial filtering velocimeter, containing the rough flow velocity of the targets. Though neither kind of data are highly accurate, Kalman Filtering is capable of integrating both position and velocity data to obtain better tracking results.
引用
收藏
页码:15 / 21
页数:7
相关论文
共 50 条
  • [1] Video-based traffic monitoring system
    Chang, ECP
    ENHANCED AND SYNTHETIC VISION 1998, 1998, 3364 : 273 - 277
  • [2] Video-based System Development for Automatic Traffic Monitoring
    Perkasa, Okaswara
    Widyantoro, Dwi H.
    2014 International Conference on Electrical Engineering and Computer Science (ICEECS), 2014, : 240 - 244
  • [3] An Optimized Video-based Traffic Congestion Monitoring System
    Zhu, Fei
    Li, Liangyou
    THIRD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING: WKDD 2010, PROCEEDINGS, 2010, : 150 - 153
  • [4] Video-based Traffic Flow Parameters Monitoring and Integrated Traffic Information System
    Zheng, Shukang
    Li, Min
    Zhu, Qi
    Liu, Xiaomin
    Shen, Haodong
    Zhang, Xuewu
    Zhang, Zhuo
    Fan, Xinnan
    PROGRESS IN MECHATRONICS AND INFORMATION TECHNOLOGY, PTS 1 AND 2, 2014, 462-463 : 77 - 84
  • [5] Intelligent Video-Based Monitoring of Freeway Traffic
    Al-Gami, Saad M.
    Abdennour, Adel A.
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 14, 2006, 14 : 279 - 285
  • [6] Analysis of Video-Based Microscopic Particle Trajectories Using Kalman Filtering
    Wu, Pei-Hsun
    Agarwal, Ashutosh
    Hess, Henry
    Khargonekar, Pramod P.
    Tseng, Yiider
    BIOPHYSICAL JOURNAL, 2010, 98 (12) : 2822 - 2830
  • [7] A Video-based Traffic Congestion Monitoring System Using Adaptive Background Subtraction
    Zhu, Fei
    PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON ELECTRONIC COMMERCE AND SECURITY, VOL II, 2009, : 73 - 77
  • [8] Optimization of Image Processing in Video-based Traffic Monitoring
    Zhu, Fei
    Ning, Jiamin
    Ren, Yong
    Peng, Jingyu
    ELEKTRONIKA IR ELEKTROTECHNIKA, 2012, 18 (08) : 91 - 96
  • [9] A video-based traffic information extraction system
    Li, PH
    Ding, LY
    Liu, JL
    IEEE IV2003: INTELLIGENT VEHICLES SYMPOSIUM, PROCEEDINGS, 2003, : 528 - 532
  • [10] A Video-based Traffic Violation Detection System
    Wang, Xiaoling
    Meng, Li-Min
    Zhang, Biaobiao
    Lu, Junjie
    Du, K. -L.
    PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC), 2013, : 1191 - 1194