• DocumentCode
    1702404
  • Title

    Robust Traffic State Estimation on Smart Cameras

  • Author

    Pletzer, Felix ; Tusch, Roland ; Böszörmenyi, Laszlo ; Rinner, Bernhard

  • Author_Institution
    Lakeside Labs., Alpen-Adria-Univ. Klagenfurt, Klagenfurt, Austria
  • fYear
    2012
  • Firstpage
    434
  • Lastpage
    439
  • Abstract
    This paper presents a novel method for video-based traffic state detection on motorways performed on smart cameras. Camera calibration parameters are obtained from the known length of lane markings. Mean traffic speed is estimated from Kanade-Lucas-Tomasi (KLT) optical flow method using a robust outlier detection. Traffic density is estimated using a robust statistical counting method. Our method has been implemented on an embedded smart camera and evaluated under different road and illumination conditions. It achieves a detection rate of more than 95% for stationary traffic.
  • Keywords
    cameras; image sequences; intelligent sensors; state estimation; statistical analysis; traffic engineering computing; video signal processing; KLT optical flow method; camera calibration parameters; detection rate; embedded smart camera; illumination conditions; kanade-lucas-tomasi optical flow method; lane markings; mean traffic speed; motorways; road conditions; robust outlier detection; robust traffic state estimation; stationary traffic; video-based traffic state detection; Cameras; Estimation; Roads; Smart cameras; Streaming media; Vectors; Vehicles; embedded computer vision; smart cameras; traffic state detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal-Based Surveillance (AVSS), 2012 IEEE Ninth International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-2499-1
  • Type

    conf

  • DOI
    10.1109/AVSS.2012.63
  • Filename
    6328053