• DocumentCode
    2039003
  • Title

    Design and implementation of a moving object tracking system

  • Author

    Enzeng Dong ; Shengxu Yan ; Jigang Tong ; Kuixiang Wei

  • Author_Institution
    Complex Syst. Control Theor. & Applic. Key Lab., Tianjin Univ. of Technol. (TUT), Tianjin, China
  • fYear
    2015
  • fDate
    2-5 Aug. 2015
  • Firstpage
    274
  • Lastpage
    279
  • Abstract
    By combining the classic object detection and tracking algorithms, this paper proposed an automatic detection and tracking algorithm on moving object. The Gaussian mixture model (GMM) is applied to detect object, and the fusion algorithm of Kalman filter and Camshift algorithm is utilized to track object. The Pan/Tile/Zoom (PTZ) control algorithm is used to adjust the PTZ Camera parameters, such as camera rotate and Zoom, which can make the object to locate in the centre of field. The effective of algorithm proposed was verified by hardware experiment platform. The experiment results show that the system designed can automatically detect and track moving object, overcoming the limit of camera view and expanding the scope of tracking to camera. Real-time and accuracy of the system has also been validated.
  • Keywords
    Gaussian processes; Kalman filters; cameras; image filtering; image fusion; image motion analysis; mixture models; object detection; object tracking; Camshift algorithm; GMM; Gaussian mixture model; Kalman filter; PTZ camera parameters; PTZ control algorithm; camera rotation; camera view; camera zoom; fusion algorithm; moving object tracking system; object detection algorithm; object location; pan-tilt-zoom control algorithm; Algorithm design and analysis; Cameras; Gaussian mixture model; Kalman filters; Mathematical model; Prediction algorithms; Gaussian mixture model; Kalman and Camshift; PTZ control; tracking system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-7097-1
  • Type

    conf

  • DOI
    10.1109/ICMA.2015.7237496
  • Filename
    7237496