• DocumentCode
    252270
  • Title

    Computer vision based real-time vehicle tracking and classification system

  • Author

    Pena-Gonzalez, Raul Humberto ; Nuno-Maganda, Marco Aurelio

  • Author_Institution
    Univ. Politec. de Victoria, Ciudad Victoria, Mexico
  • fYear
    2014
  • fDate
    3-6 Aug. 2014
  • Firstpage
    679
  • Lastpage
    682
  • Abstract
    Detect, classify and keep track, in real-time, on different kinds of objects or vehicles that are moving on a road is crucial for traffic managements systems, among other research areas. In this paper, a vision based system to detect, track, count and classify moving vehicles, on any kind of road, is shown. The data acquisition system consists of a HD-RGB camera placed on the road, while the information processing is performed by clustering and classification algorithms. The system obtained an efficiency score over the 95 percent in test cases, as well, the correct classification of 85 percent of the test objects. Also, the system achieves 30 fps in image processing with a resolution of 1280×720.
  • Keywords
    cameras; computer vision; data acquisition; image classification; image motion analysis; object detection; object tracking; pattern clustering; road vehicles; traffic engineering computing; HD-RGB camera; clustering algorithm; computer vision; data acquisition system; information processing; moving vehicle classification; moving vehicle counting; moving vehicle detection; real-time moving vehicle tracking; real-time vehicle classification system; traffic management systems; vision based system; Cameras; Computer vision; Machine vision; Real-time systems; Roads; Vehicle detection; Vehicles; Computer Vision; Image Classification; Traffic Estimation; Vehicle Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (MWSCAS), 2014 IEEE 57th International Midwest Symposium on
  • Conference_Location
    College Station, TX
  • ISSN
    1548-3746
  • Print_ISBN
    978-1-4799-4134-6
  • Type

    conf

  • DOI
    10.1109/MWSCAS.2014.6908506
  • Filename
    6908506