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
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;
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
DOI :
10.1109/ICEGIC.2010.5716876
