• DocumentCode
    465882
  • Title

    Vision-Based Front Vehicle Detection and Its Distance Estimation

  • Author

    Chang, Jyh-Yeong ; Cho, Chien-Wen

  • Author_Institution
    Nat. Chiao-Tung Univ., Hsin-Chu
  • Volume
    3
  • fYear
    2006
  • fDate
    8-11 Oct. 2006
  • Firstpage
    2063
  • Lastpage
    2068
  • Abstract
    Vision-based driver assistant systems are very promising in Intelligent Transportation System (ITS). This paper will propose a system that can detect front vehicles and estimate the nearest car distance from the host car. In a companion paper, we have developed a scene analysis module that deals with scene segmentation and natural object labeling of forward-looking images by the use of fuzzy adaptive resonance theory (ART) and fuzzy inference techniques. Based on this technique, the proposed system can detect the front vehicles and then estimate the distance of the nearest car from us. The validity of our proposed scheme in car detection and the distance estimation was verified to be very successful by field-test experiments.
  • Keywords
    adaptive resonance theory; automated highways; fuzzy reasoning; image segmentation; Intelligent Transportation System; car detection; distance estimation; fuzzy adaptive resonance theory; fuzzy inference techniques; scene segmentation; vision-based driver assistant systems; vision-based front vehicle detection; Image analysis; Intelligent transportation systems; Laser radar; Layout; Pixel; Radar detection; Radar imaging; Roads; Subspace constraints; Vehicle detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    1-4244-0099-6
  • Electronic_ISBN
    1-4244-0100-3
  • Type

    conf

  • DOI
    10.1109/ICSMC.2006.385164
  • Filename
    4274170