Accurate Camera Calibration for Off-line, Video-Based Augmented
Reality
Simon Gibson, Jon Cook, Toby Howard, Roger Hubbold, and Dan
Oram.
IEEE and ACM International Symposium on Mixed and Augmented Reality
(ISMAR 2002), Darmstadt, Germany, September 2002 (to appear).
Abstract
Camera tracking is a fundamental requirement for video-based Augmented
Reality applications. The ability to accurately calculate the
intrinsic and extrinsic camera parameters for each frame of a video
sequence is essential if synthetic objects are to be integrated into
the image data in a believable way. In this paper, we present an
accurate and reliable approach to camera calibration for off-line
video-based Augmented Reality applications.
We first describe an improved feature tracking algorithm, based on the
widely used Kanade-Lucas-Tomasi tracker. Estimates of inter-frame
camera motion are used to guide tracking, greatly reducing the number
of incorrectly tracked features. We then present a robust hierarchical
scheme that merges sub-sequences together to form a complete
projective reconstruction. Finally, we describe how RANSAC-based
random sampling can be applied to the problem of self-calibration,
allowing for more reliable upgrades to metric geometry. Results of
applying our calibration algorithms are given for both synthetic and
real data.
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