• DocumentCode
    1941742
  • Title

    Obstacle detection for start-inhibit and low speed driving

  • Author

    Bertozzi, M. ; Broggi, A. ; Medici, P. ; Porta, P.P. ; Vitulli, R.

  • Author_Institution
    Dipt. di Ingegneria dell´´Informazione, Parma Univ., Italy
  • fYear
    2005
  • fDate
    6-8 June 2005
  • Firstpage
    569
  • Lastpage
    574
  • Abstract
    The work described in this paper has been developed in the framework of the integrated project APALACI-PReVENT, a research activity funded by the European Commission to contribute to road safety by developing and demonstrating preventive safety technologies and applications. The goal of the system presented in this work is the development of a vision system for detecting potential obstacles in front of a slowly moving or still vehicle. When the vehicle is still, a background subtraction approach is used assuming that the background keeps stationary for a limited amount of time; thus, a reference background is computed and used to detect changes into the scene. A different approach is used when the vehicle is moving. The system, by means of inertial sensors, can detect ego-motion and correct background information accordingly. A temporal stereo match technique, able to detect obstacles in moving situations, completes the system. According to experimental results, the proposed algorithm can be useful in different automotive applications, requiring real-time segmentation without assumptions on background motion.
  • Keywords
    computer vision; driver information systems; image matching; image motion analysis; image segmentation; image sensors; object detection; real-time systems; road safety; road vehicles; stereo image processing; APALACI-PReVENT; automotive application; background subtraction approach; ego-motion detection; inertial sensors; low speed driving; obstacle detection; preventive safety; real-time segmentation; road safety; temporal stereo match technique; vehicle movement; vision system; Accidents; Cameras; Image segmentation; Layout; Machine vision; Object detection; Pixel; Predictive models; Road safety; Vehicle detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2005. Proceedings. IEEE
  • Print_ISBN
    0-7803-8961-1
  • Type

    conf

  • DOI
    10.1109/IVS.2005.1505164
  • Filename
    1505164