• DocumentCode
    2822326
  • Title

    Algorithm Study for Pedestrian Detection Based on Monocular Vision

  • Author

    Lie, Guo ; Rong-ben, Wang ; Li-sheng, Jin ; Lin-hui, Li ; Lu, Yang

  • Author_Institution
    Jilin Univ., Changchun
  • fYear
    2006
  • fDate
    13-15 Dec. 2006
  • Firstpage
    83
  • Lastpage
    87
  • Abstract
    For intelligent vehicle and driving assistant system, pedestrian detection technology is an important research held to avoid dangerous traffic accidents. This article puts forward a pedestrian detection algorithm based on edge symmetry. First, lane recognition method is used to get area of interest (AOI) ahead of vehicle. Second, as pedestrian legs have prominent vertical edge symmetry, their symmetrical axis can be acquired through vertical edge extraction in the AOI. Combined with pedestrian transcendental features, the candidate pedestrian could be locked. Third, the candidate pedestrian will be validated based on the gray symmetry and local entropy. The experiment results show that the algorithm is effective, reliable and robust.
  • Keywords
    automated highways; computer vision; driver information systems; edge detection; road accidents; road traffic; road vehicles; dangerous traffic accident avoidance; driving assistant system; gray symmetry; intelligent vehicle; lane recognition method; local entropy; monocular vision; pedestrian detection algorithm; vertical edge extraction; Detection algorithms; Educational institutions; Entropy; Leg; Road accidents; Support vector machines; Transportation; Vehicle detection; Vehicle driving; Vehicles; Driver Assistance System; Machine Vision; Pedestrian Detection; Symmetry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Electronics and Safety, 2006. ICVES 2006. IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    1-4244-0759-1
  • Electronic_ISBN
    1-4244-0759-1
  • Type

    conf

  • DOI
    10.1109/ICVES.2006.371559
  • Filename
    4233995