Accurate pose estimation using single marker single camera calibration system
Pati S, Erat O, Wang L, Weidert S, Euler E, Navab N, Fallavollita P (2013)
Publication Type: Conference contribution
Publication year: 2013
Journal
Book Volume: 8671
Conference Proceedings Title: Proceedings of SPIE - The International Society for Optical Engineering
Event location: USA
ISBN: 9780819494450
DOI: 10.1117/12.2006776
Abstract
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. © 2013 SPIE.
Involved external institutions
Germany (DE)How to cite
APA:
Pati, S., Erat, O., Wang, L., Weidert, S., Euler, E., Navab, N., & Fallavollita, P. (2013). Accurate pose estimation using single marker single camera calibration system. In Proceedings of SPIE - The International Society for Optical Engineering. USA.
MLA:
Pati, Sarthak, et al. "Accurate pose estimation using single marker single camera calibration system." Proceedings of the Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, USA 2013.
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