Classical nonlinear methods for finding the relative orientation between a camera and an object suffer from considerable computation time and requirement for a good initial estimate, while linear methods, which do not need an initial estimate, are sensitive to noise and outliers. In this paper, we study the performances of different solution methods in the presence of noise and outliers. We also present a new iterative algorithm which is efficient, globally convergent, and relatively robust to noise and outliers.

Date Published: 13 October 1994
PDF: 12 pages
Proc. SPIE 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, (13 October 1994); doi: 10.1117/12.189090

Published in SPIE Proceedings Vol. 2354:
Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision
David P. Casasent, Editor(s)