Two Linear Methods for Camera Calibration and Their Applications to Augmented Reality and 3D Reconstruction
This paper presents two new compact camera calibration methods: one is derived from a calibration pattern that consists of two planes orthogonal to each other; the other is derived from a calibration pattern that consists of three planar patterns which need not to be orthogonal. In particular, these methods allow to vary the intrinsic parameters of a camera. In order to demonstrate the effectiveness of the proposed methods, two camera calibration methods are applied to an augmented reality system with a moving zoom lens camera and a 3D reconstruction system respectively. Two applications have shown that the proposed methods are reliable.
- R. T. Azuma and G. Bishop, “Improving static and dynamic registration in an optical see through display”, In Proc. SIGGRAPH’94, pages 194–204.Google Scholar
- R. Hartely and A. Zissermann, Multiple View Geometry in Computer Vision, Cambridge University Press, 2000.Google Scholar
- G. Simon and M.-O. Berger, “A Two-stage Robust Statistical Method for Temporal Registration from Features of Various Type”, In Proc. ICCV’98, pages 261–266.Google Scholar
- B. Triggs, “Auto-calibration and the absolute quadric”, In Proc. IEEE Conference on Computer Vision and Pattern Recognition, pages 609–614, 1997.Google Scholar
- M. Uenohara and T. Kanade, “Vision based object registration for real time image overlay”, Journal of Computers in Biology and Medecine, 1996.Google Scholar