• DocumentCode
    2562475
  • Title

    A framework for camera pose tracking using stochastic data fusion

  • Author

    Moemeni, Armaghan ; Tatham, Eric

  • Author_Institution
    Dept. of Media Technol., De Montfort Univ., Leicester, UK
  • fYear
    2010
  • fDate
    21-23 Dec. 2010
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    A novel camera pose tracking system using a stochastic inertial-visual sensor fusion has been proposed. A method based on the Particle Filtering concept has been adapted for inertial and vision data fusion, which benefits from the agility of inertial-based tracking and robustness of vision-based camera tracking.
  • Keywords
    augmented reality; cameras; computer vision; particle filtering (numerical methods); pose estimation; sensor fusion; stochastic processes; tracking; augmented reality; camera pose tracking system; inertial-based tracking; particle filtering concept; stochastic data fusion; stochastic inertial-visual sensor fusion; vision data fusion; vision-based camera tracking; Acceleration; Accelerometers; Angular velocity; Cameras; Filtering; Games; Tracking; augmented reality; camera pose tracking; inertial-visual sensor fusion; particle filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Games Innovations Conference (ICE-GIC), 2010 International IEEE Consumer Electronics Society's
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-7178-2
  • Electronic_ISBN
    978-1-4244-7179-9
  • Type

    conf

  • DOI
    10.1109/ICEGIC.2010.5716876
  • Filename
    5716876