• DocumentCode
    3549148
  • Title

    ARTag, a fiducial marker system using digital techniques

  • Author

    Fiala, Mark

  • Author_Institution
    Nat. Res. Council of Canada, Ottawa, Ont., Canada
  • Volume
    2
  • fYear
    2005
  • fDate
    20-25 June 2005
  • Firstpage
    590
  • Abstract
    Fiducial marker systems consist of patterns that are mounted in the environment and automatically detected in digital camera images using an accompanying detection algorithm. They are useful for augmented reality (AR), robot navigation, and general applications where the relative pose between a camera and object is required. Important parameters for such marker systems is their false detection rate (false positive rate), their inter-marker confusion rate, minimal detection size (in pixels) and immunity to lighting variation. ARTag is a marker system that uses digital coding theory to get a very low false positive and inter-marker confusion rate with a small required marker size, employing an edge linking method to give robust lighting variation immunity. ARTag markers are bi-tonal planar patterns containing a unique ID number encoded with robust digital techniques of checksums and forward error correction (FEC). This proposed new system, ARTag has very low and numerically quantifiable error rates, does not require a grey scale threshold as does other marker systems, and can encode up to 2002 different unique ID´s with no need to store patterns. Experimental results are shown validating this system.
  • Keywords
    augmented reality; forward error correction; image coding; image recognition; ARTag; augmented reality; bi-tonal planar pattern; checksums; digital camera images; digital technique; fiducial marker system; forward error correction; image detection algorithm; Augmented reality; Codes; Detection algorithms; Digital cameras; Forward error correction; Joining processes; Navigation; Robot vision systems; Robotics and automation; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-2372-2
  • Type

    conf

  • DOI
    10.1109/CVPR.2005.74
  • Filename
    1467495