• DocumentCode
    3466731
  • Title

    Robust obstacle detection with monocular vision based on motion analysis

  • Author

    Demonceaux, C. ; Kachi-Akkouche, D.

  • Author_Institution
    CREA, Amiens, France
  • fYear
    2004
  • fDate
    14-17 June 2004
  • Firstpage
    527
  • Lastpage
    532
  • Abstract
    This paper deals with the problem of obstacle detection from a single camera mounted on a vehicle. We define an obstacle as any object that obstructs the vehicle´s driving path. The perception of the environment is performed through a fast processing of image sequence. The approach is based on motion analysis. Generally, the optical flow techniques are huge in computation time and sensitive to vehicle motion. To overcome these problems, we choose to detect the obstacle in two steps. The road motion is firstly computed through a fast and robust wavelets analysis. Then, we detect the areas which have a different motion thanks to a Bayesian modelization. Results shown in the paper prove that the proposed method permits the detection of any obstacle on a road.
  • Keywords
    Bayes methods; Markov processes; computer vision; image segmentation; image sequences; motion compensation; motion estimation; object detection; road vehicles; roads; wavelet transforms; Bayesian modelization; camera; image processing; image sequence; monocular vision; motion analysis; obstacle detection; optical flow techniques; road motion; robust obstacle detection; vehicle driving path; vehicle motion; wavelets analysis; Cameras; Image motion analysis; Image sequences; Motion analysis; Motion detection; Optical sensors; Roads; Robustness; Vehicle detection; Vehicle driving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2004 IEEE
  • Print_ISBN
    0-7803-8310-9
  • Type

    conf

  • DOI
    10.1109/IVS.2004.1336439
  • Filename
    1336439