• DocumentCode
    3033929
  • Title

    Following vehicle detection using multiple cameras

  • Author

    Inoue, Osamu ; Ahn, Seonju ; Ozawa, Shinji

  • Author_Institution
    Keio Univ., Tokyo
  • fYear
    2008
  • fDate
    22-24 Sept. 2008
  • Firstpage
    79
  • Lastpage
    83
  • Abstract
    In recent days, various in-vehicle camera systems have been proposed for detecting following vehicles. In this paper, we propose a vehicle detection method based on feature points. First, the feature points are detected from the image obtained from the camera and the optical flow is calculated by tracking the feature points across the image sequence. Then the feature points are assumed to be coplanar and to model the front of the following vehicle. This plane´s movement can be defined by an affine-transformation, and the optical flow of the plane is used to determine whether a section of the image is in the background or is part of the following vehicle. By extending previous detection systems based on edge models to include feature point tracking, our method is able to produce improved detection of following vehicles. To verify the accuracy of our method, we have performed experiments in a variety of different road conditions and situations. As a result, the proposed system is expected to be useful for reducing traffic accidents caused by rear- and/or side-located vehicles.
  • Keywords
    cameras; image motion analysis; image sequences; object detection; feature point tracking; image sequence; in-vehicle camera system; multiple cameras; optical flow; vehicle detection; Cameras; Image edge detection; Image motion analysis; Layout; Road accidents; Robustness; Safety; Vehicle detection; Vehicle driving; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Electronics and Safety, 2008. ICVES 2008. IEEE International Conference on
  • Conference_Location
    Columbus, OH
  • Print_ISBN
    978-1-4244-2359-0
  • Electronic_ISBN
    978-1-4244-2360-6
  • Type

    conf

  • DOI
    10.1109/ICVES.2008.4640892
  • Filename
    4640892