Title :
EyeTap video-based featureless projective motion estimation assisted by gyroscopic tracking
Author :
Aimone, Chris ; Marjan, Andrewj ; Mann, Steve
Author_Institution :
Toronto Univ., Ont., Canada
Abstract :
This paper proposes a computationally economical method of recovering the projective motion of head mounted cameras or EyeTap devices, for use in wearable computer mediated reality. The tracking system combines featureless vision and inertial tracking in a closed loop system to achieve accurate robust head tracking using inexpensive uncalibrated sensors. The combination of inertial and vision techniques provides the high accuracy visual registration needed for fitting computer graphics onto real images and robustness to large interframe camera motion due to fast head rotations. Operating on a 1.2 GHz Pentium III wearable computer, the system is able to register live video images with less than 2 pixels of error (0.3 degrees) at 12 frames per second.
Keywords :
augmented reality; closed loop systems; motion estimation; wearable computers; 1.2 GHz Pentium III wearable computer; EyeTap video-based featureless projective motion estimation; closed loop system; computationally economical method; gyroscopic tracking; head mounted cameras; inertial tracking; interframe camera motion; projective motion; robust head tracking; visual registration; wearable computer mediated reality; Cameras; Closed loop systems; Head; Machine vision; Motion estimation; Robustness; Sensor systems; Tracking loops; Wearable computers; Wearable sensors;
Conference_Titel :
Wearable Computers, 2002. (ISWC 2002). Proceedings. Sixth International Symposium on
Print_ISBN :
0-7695-1816-8
DOI :
10.1109/ISWC.2002.1167223