• DocumentCode
    2571344
  • Title

    Viewpoint independent vehicle speed estimation from uncalibrated traffic surveillance cameras

  • Author

    Mao, Haili ; Ye, Chengxi ; Song, Mingli ; Bu, Jiajun ; Li, Na

  • Author_Institution
    Coll. of Comput. Sci., Zhejiang Univ., Hangzhou, China
  • fYear
    2009
  • fDate
    11-14 Oct. 2009
  • Firstpage
    4920
  • Lastpage
    4925
  • Abstract
    We present here a prototype of an algorithm for vehicle speed estimation. Different from previous approaches, our algorithm requires no road markers and fewer manual calibrations. Based on specific projection rules, we find a relation between the in-camera coordinate and the real world coordinate. A non-linear regression is employed to estimate the model parameters. This model enables us to estimate the real world position of the vehicles directly from a video sequence taken by a surveillance camera. The algorithm shows its ability to produce accurate estimations in our experiments.
  • Keywords
    image sequences; parameter estimation; road traffic; road vehicles; video cameras; model parameter estimation; nonlinear regression; uncalibrated traffic surveillance cameras; video sequence; viewpoint independent vehicle speed estimation; Calibration; Cameras; Land vehicles; Parameter estimation; Radar tracking; Road vehicles; Surveillance; Traffic control; Vehicle detection; Video sequences; Kalman filter; Vehicle speed estimate; camera calibration; projection model; surveillance camera; tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4244-2793-2
  • Electronic_ISBN
    1062-922X
  • Type

    conf

  • DOI
    10.1109/ICSMC.2009.5346288
  • Filename
    5346288