• DocumentCode
    457531
  • Title

    Robust vehicle detection based on shadow classification

  • Author

    Lee, Deaho ; Park, Youngtae

  • Author_Institution
    Fac. of Gen. Educ., Kyung Hee Univ.
  • Volume
    3
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1167
  • Lastpage
    1170
  • Abstract
    The multi-level shadow classification has been shown to provide reliable information on the presence of vehicles in traffic scenes. The method is based on classifying the shadow shapes into six categories at each threshold level. Non-overlapping shadow shapes with higher priority are selected at each level. Shadow-reshaping capability makes the resulting shadow information robust to the variation of operating conditions. Unlike other approaches, vehicle movement information between frames is not utilized; thereby the traffic parameters can be measured quantitatively even when the vehicle movement is not observed. Also the detecting performance is not affected by the abrupt change of weather because background information is not utilized
  • Keywords
    image classification; object detection; road vehicles; traffic engineering computing; multilevel shadow classification; reliable information; robust vehicle detection; shadow information; shadow-reshaping capability; traffic parameters; vehicle movement information; Automotive engineering; Cameras; Layout; Monitoring; Reliability engineering; Robustness; Shape; Traffic control; Vehicle detection; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.1018
  • Filename
    1699733