Contraction mapping calibration

Authors:
Nicolas Guilbert;Anders Heyden
Affiliations:
Lund Institute of Technology;Division of Mathematics, Malmö University, Sweden
Venue:
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Year:
2005

Citing 2
Cited 0

Self-calibration of an affine camera from multiple views

International Journal of Computer Vision
Euclidean Reconstruction from Image Sequences with Varying and Unknown Focal Length and Principal Point

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper a new calibration scheme for recovering Euclidian camera parameters from their affine of projective primitives is presented. It is based on a contraction mapping implying that the obtained solution is unique, i.e. no local minimas threaten to yield a non-optimal solution. The approach unifies Euclidian calibration from affine and projective configurations and fewer cameras (m ≥ 2) need to be available than in traditional schemes. The algorithm is validated on synthetic and real data.