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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2012  >  12(4): 107-113
LOU Lu, ZHAO Ling, GENG Tao. Detecting and tracking method of moving vehicle[J]. Journal of Traffic and Transportation Engineering, 2012, 12(4): 107-113. doi: 10.19818/j.cnki.1671-1637.2012.04.014
Citation: LOU Lu, ZHAO Ling, GENG Tao. Detecting and tracking method of moving vehicle[J]. Journal of Traffic and Transportation Engineering, 2012, 12(4): 107-113. doi: 10.19818/j.cnki.1671-1637.2012.04.014
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Detecting and tracking method of moving vehicle

doi: 10.19818/j.cnki.1671-1637.2012.04.014
  • 1.

    School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China

  • 2.

    Department of Computer Science, Aberystwyth University, Aberystwyth SY23 3DB, Ceredigion, UK

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  • Author Bio:

    LOU Lu(1969-), male, lecturer, +86-23-62652751, cloudlou@163.com

  • Received Date: 2012-02-13
  • Publish Date: 2012-08-25
    Abstract
  • In order to improve the comprehensive management ability of intelligent transportation systems in cities, a detecting and tracking method of moving vehicle was presented by using video analysis. Considering the pavement environment of urban transport artery and the difference between moving object and the statistical characteristics for road background, an adaptive background updating algorithm was realized based on Bayesian probability criterion, from which foreground image was extracted. Motion detection and real-time tracking were realized for target vehicle in video sequence based on Kalman filter. The traffic flow video collected from a certain urban transport artery of Chongqing was detected by using the proposed method. Experimental result indicates that the video with normal resolution can be processed in time by using the method, and the average detecting accuracy is 94 %, so the proposed method has good real-time performance and robustness, and meets the requirement of real- time detecting and tracking vehicles in urban traffic arteries. 2 tabs, 5 figs, 15 refs.

     

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    • References(15)
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