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Proceedings Paper

Accurate pose estimation using single marker single camera calibration system
Author(s): Sarthak Pati; Okan Erat; Lejing Wang; Simon Weidert; Ekkehard Euler; Nassir Navab; Pascal Fallavollita
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Paper 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.

Paper Details

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
Show Author Affiliations
Sarthak Pati, Technische Univ. München (Germany)
Okan Erat, Technische Univ. München (Germany)
Lejing Wang, Technische Univ. München (Germany)
Simon Weidert, Ludwig-Maximilians-Univ. München (Germany)
Ekkehard Euler, Ludwig-Maximilians-Univ. München (Germany)
Nassir Navab, Technische Univ. München (Germany)
Pascal Fallavollita, Technische Univ. München (Germany)


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

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