• DocumentCode
    3579922
  • Title

    Traffic cone detection and localization in TechX Challenge 2013

  • Author

    Lubing Zhou ; Han Wang ; Danwei Wang ; Lihua Xie ; Keng Peng Tee

  • Author_Institution
    Inst. for Infocomm Res., A*STAR, Singapore, Singapore
  • fYear
    2014
  • Firstpage
    54
  • Lastpage
    58
  • Abstract
    This paper presents the detection and localization methods of entrance and staircase markers for the team E-Mobile in TechX Challenge 2013. Autonomous vehicles are required to detect and locate traffic cones beside the indoor entrance and staircase. One big challenge is from the unpredictable lighting conditions and environment. Different practical techniques such as color space selection, segmentation, shape analysis, distance estimation, and detector training are combined to obtain good detection rate and localization accuracy. The proposed methods can achieve satisfactory performance in real-world experiments.
  • Keywords
    image colour analysis; image segmentation; mobile robots; object detection; robot vision; shape recognition; telerobotics; TechX Challenge 2013; autonomous vehicles; color space selection; detector training; distance estimation; entrance markers; segmentation; shape analysis; staircase markers; team E-Mobile; traffic cone detection; traffic cone localization; unpredictable lighting conditions; Accuracy; Detectors; Image color analysis; Lighting; Robots; Shape; Training; autonomous vehicle; object detection; object localization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2014 13th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICARCV.2014.7064279
  • Filename
    7064279