Automated Camera Calibration and 3D Egomotion Estimation
for Augmented Reality Applications
Dieter Koller ,
Gudrun Klinker,
Eric Rose,
David Breen,
Ross Whitaker, and
Mihran Tuceryan
In Proceedings of the 7th International Conference
on Computer Analysis of Images and Patterns (CAIP-97), Kiel, Germany,
September 10-12, 1997, pp. 199-206.
Abstract
This paper addresses the problem of accurately tracking the 3D motion of
a monocular camera in a known 3D environment and dynamically estimating the
3D camera location. For that purpose we propose a fully automated
landmark-based
camera calibration method and initialize a motion estimator, which employes
extended Kalman filter techniques to track landmarks and to estimate the
camera location at any given time.
The implementation of our approach has been proven to be efficient and
robust and
our system successfully tracks in real-time at approximately 10~Hz.
We show tracking results of various augmented reality scenarios.
The document is available online as
zipped postscript (1446586 Bytes).
Last modified on Thursday, June 12, 1997,
Dieter Koller
(koller@vision.caltech.edu)