• DocumentCode
    3353465
  • Title

    Video Tracker System for Traffic Monitoring and Analysis

  • Author

    Ocakli, Mehmet ; Demirekler, Mübeccel

  • Author_Institution
    Gudum Kontrol Labaratuvari, Ankara, Turkey
  • fYear
    2007
  • fDate
    11-13 June 2007
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this study, a new algorithm is proposed to solve the multi-vehicle tracking problem that can deal with problems such as occlusion, short period object lost or inaccurate object detection. The scene, which is inspected in this study, is an uncontrolled junction with high traffic density where the above defined problems occur frequently. The developed system is a system that collects a-priory information about the junction, models that a-priory information and uses it in the tracking stage. The a-priory information collecting stage of the system is done automatically. Two different tracking methods are used together in the developed system: The multi-model Kalman tracker and the Markov scene partition tracker. The Markov scene partition tracker is used to increase the performance of the multi-model Kalman tracker. By this combination of the two trackers the continuity of the track is achieved for situations such as object loss and occlusion.
  • Keywords
    Markov processes; object detection; tracking; traffic engineering computing; video signal processing; Markov scene partition tracker; high traffic density; multimodel Kalman tracker; multivehicle tracking problem; traffic analysis; traffic monitoring; video tracker system; Kalman filters; Layout; Monitoring; Object detection; Robots; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications, 2007. SIU 2007. IEEE 15th
  • Conference_Location
    Eskisehir
  • Print_ISBN
    1-4244-0719-2
  • Electronic_ISBN
    1-4244-0720-6
  • Type

    conf

  • DOI
    10.1109/SIU.2007.4298554
  • Filename
    4298554