• DocumentCode
    3483830
  • Title

    Research on traffic moving object detection, tracking and track-generating

  • Author

    Lin, Shanming ; Tang, Jun ; Zhang, Xuewu ; Lv, Yanyun

  • Author_Institution
    Comput. & Inf. Eng. Coll., Hohai Univ., Changzhou, China
  • fYear
    2009
  • fDate
    5-7 Aug. 2009
  • Firstpage
    783
  • Lastpage
    788
  • Abstract
    This paper presents algorithms for vision-based detection, tracking and trajectory generation of vehicles in simple video sequences of traffic scenes which are registered by a stationary camera. Processing is done by three steps: improved vehicle detection method, faster tracking algorithm and new vehicle trajectory generation technique. Vehicles are viewed as rectangular blocks with certain active action. The propounded method is based on the correspondences between regions and vehicles, as the vehicles moving through the video sequence. The vehicle trajectory generation technique, used for gathering statistical traffic data for analysis in vehicle flow detection, is also described in detail. Experimental results from highway scenes demonstrate the effectiveness of the vehicle detection and tracking method.
  • Keywords
    computer vision; image motion analysis; image sequences; object detection; road traffic; road vehicles; statistical analysis; tracking; traffic engineering computing; video signal processing; statistical analysis; traffic moving object detection; vehicle flow detection; vehicle tracking algorithm; vehicle trajectory generation; video sequences; vision-based detection; Data mining; Layout; Object detection; Optical sensors; Probability distribution; Target tracking; Trajectory; Vehicle detection; Vehicle dynamics; Vehicles; Object detection; Object tracking; Trajectory generating; Vehicle flow detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4244-4794-7
  • Electronic_ISBN
    978-1-4244-4795-4
  • Type

    conf

  • DOI
    10.1109/ICAL.2009.5262818
  • Filename
    5262818