• DocumentCode
    1725539
  • Title

    Accelerating Template-Based Matching on the GPU for AR Applications

  • Author

    Allusse, Yannick ; Grasset, Raphäel ; Billinghurst, Mark

  • Author_Institution
    HIT Lab. NZ, Univ. of Canterbury, Christchurch
  • fYear
    2007
  • Firstpage
    271
  • Lastpage
    272
  • Abstract
    Recently researchers have shown that it is possible to use GPU hardware for image processing and computer vision algorithms. We have been exploring how to use GPU hardware to improve marker- based tracking for AR Applications. In this paper we describe our findings and explored issues in the context of a standard fiducial tracking pipeline. We demonstrate the implementation of a template matching process on the GPU and the performance improvement gained in comparison to a traditional CPU implementation.
  • Keywords
    augmented reality; computer graphics; computer vision; image matching; AR applications; GPU hardware; augmented reality; computer vision; fiducial tracking pipeline; image processing; marker-based tracking; template-based matching; Acceleration; Application software; Computer vision; Costs; Hardware; Image processing; Libraries; Pattern matching; Pipelines; Robustness; I.4.8 [Computing Methodologies]: Image Processing and Computer Vision¿Scene Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mixed and Augmented Reality, 2007. ISMAR 2007. 6th IEEE and ACM International Symposium on
  • Conference_Location
    Nara
  • Print_ISBN
    978-1-4244-1749-0
  • Electronic_ISBN
    978-1-4244-1750-6
  • Type

    conf

  • DOI
    10.1109/ISMAR.2007.4538862
  • Filename
    4538862