Visual marker based tracking is one of the most widely used tracking techniques in Augmented Reality (AR) applications. Generally, multiple square markers are needed to perform robust and accurate tracking. Various marker based methods for calibrating relative marker poses have already been proposed. However, the calibration accuracy of these methods relies on the order of the image sequence and pre-evaluation of pose-estimation errors, making the method offline. Several studies have shown that the accuracy of pose estimation for an individual square marker depends on camera distance and viewing angle. We propose a method to accurately model the error in the estimated pose and translation of a camera using a single marker via an online method based on the Scaled Unscented Transform (SUT). Thus, the pose estimation for each marker can be estimated with highly accurate calibration results independent of the order of image sequences compared to cases when this knowledge is not used. This removes the need for having multiple markers and an offline estimation system to calculate camera pose in an AR application.

Date Published: 15 March 2013
PDF: 6 pages
Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 867126 (15 March 2013); doi: 10.1117/12.2006776

Published in SPIE Proceedings Vol. 8671:
Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes III; Ziv R. Yaniv, Editor(s)