• DocumentCode
    2118754
  • Title

    Fast gain-adaptive KLT tracking on the GPU

  • Author

    Zach, Christopher ; Gallup, David ; Frahm, Jan-Michael

  • Author_Institution
    North Carolina Univ., Chapel Hill, NC
  • fYear
    2008
  • fDate
    23-28 June 2008
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    High-performance feature tracking from video input is a valuable tool in many computer vision techniques and mixed reality applications. This work presents a refined and substantially accelerated approach to KLT feature tracking performed on the GPU. Additionally, a global gain ratio between successive frames is estimated to compensate for changes in the camera exposure. The proposed approach achieves more than 200 frames per second on state-of-the art consumer GPUs for PAL (720 times 576) resolution data, and delivers real-time performance even on low-end mobile graphics processors.
  • Keywords
    feature extraction; image processing equipment; image resolution; GPU; KLT feature tracking; global gain ratio; graphics processing unit; video input; Acceleration; Application software; Cameras; Computer vision; Graphics; Hardware; Karhunen-Loeve transforms; Pixel; Runtime; Virtual reality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    2160-7508
  • Print_ISBN
    978-1-4244-2339-2
  • Electronic_ISBN
    2160-7508
  • Type

    conf

  • DOI
    10.1109/CVPRW.2008.4563089
  • Filename
    4563089