Proceedings of the 2005 international conference on Augmented tele-existence
Center-of-mass variation under projective transformation
Pattern Recognition Letters
AR baseball presentation system with integrating multiple planar markers
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
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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.