Reliable Automatic Calibration of a Marker-Based Position Tracking System

Authors:
David Claus;Andrew W. Fitzgibbon
Affiliations:
University of Oxford, UK;University of Oxford, UK
Venue:
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Year:
2005

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Abstract

This paper describes an accurate vision-based position tracking system which is significantly more robust and reliable over a wide range of environments than existing approaches. Based on fiducial detection for robustness, we show how a machine-learning approach allows the development of significantly more reliable fiducial detection than has previously been demonstrated. We calibrate fiducial positions using a structure-from-motion solver. We then show how nonlinear optimization of the camera position during tracking gives accuracy comparable with full bundle adjustment but at significantly reduced cost.