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] Research on Vessel Positioning System Based on Kalman filtering
    Chu Guangqian
    Cao Yan
    Si Chaoliang
    INFORMATION TECHNOLOGY FOR MANUFACTURING SYSTEMS II, PTS 1-3, 2011, 58-60 : 2428 - +
  • [2] Kalman Filtering for Wearable Fitness Monitoring
    Tran, K. H.
    Chew, M. T.
    2015 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC), 2015, : 2020 - 2025
  • [3] Kalman filtering based dynamic OD matrix estimation and prediction for traffic systems
    Lin, Y
    Cai, YL
    Huang, YX
    2003 IEEE INTELLIGENT TRANSPORTATION SYSTEMS PROCEEDINGS, VOLS. 1 & 2, 2003, : 1515 - 1520
  • [4] Self-Similar Traffic Prediction Algorithm Based on An Improved Kalman Filtering
    Na, Zhenyu
    Gao, Zihe
    JOURNAL OF INTERNET TECHNOLOGY, 2011, 12 (03): : 399 - 405
  • [5] An adaptive Kalman predictor applied to tracking vehicles in the traffic monitoring system
    Qiu, ZJ
    An, DX
    Yao, DY
    Zhou, DH
    Ran, B
    2005 IEEE Intelligent Vehicles Symposium Proceedings, 2005, : 230 - 235
  • [6] Traffic Flow Prediction using Kalman Filtering Technique
    Kumar, Selvaraj Vasantha
    TRANSBALTICA 2017: TRANSPORTATION SCIENCE AND TECHNOLOGY, 2017, 187 : 582 - 587
  • [7] KALMAN FILTERING BASED MOTION ESTIMATION FOR VIDEO CODING WITH ADAPTIVE BLOCK PARTITIONING
    Luo, Yi
    Celenk, Mehmet
    2008 IEEE WORKSHOP ON SIGNAL PROCESSING SYSTEMS: SIPS 2008, PROCEEDINGS, 2008, : 129 - +
  • [8] Kalman Filter Based Tracking in an Video Surveillance System
    Suliman, Caius
    Cruceru, Cristina
    Moldoveanu, Florin
    ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, 2010, 10 (02) : 30 - 34
  • [9] Design on Airborne Positioning System Based on Improved Kalman Filtering
    Shen, Dong
    Zhao, Chaoyang
    Li, Qiang
    Huang, Xia
    PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS AND COMPUTER AIDED EDUCATION (ICISCAE 2018), 2018, : 51 - 54
  • [10] Processing of building subsidence monitoring data based on fusion Kalman filtering algorithm
    Zhang, Jing
    Liu, Hongbo
    Sun, Xiaojun
    Liu, Shangyi
    ALEXANDRIA ENGINEERING JOURNAL, 2021, 60 (03) : 3353 - 3360