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Numerical Methods for Model-Based Pose Recovery |
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@TechReport{Carceroni:TR97b,
author = {Rodrigo L. Carceroni and Christopher M. Brown},
title = {Numerical Methods for Model-Based Pose Recovery},
institution = {Comp. Sci. Dept. University of Rochester},
year = {1997},
number = {659},
address = {Rochester NY},
month = {August},
abstract = {
In this paper we review and compare several techniques for model-based pose
recovery (extrinsic camera calibration) from monocular images. We classify the
solutions reported in the literature as analytical perspective, affine and
numerical perspective. We also present reformulations for two of the most
important numerical perspective solutions: Lowe's algorithm and Phong-Horaud's
algorithm. Our improvement to Lowe's algorithm consists of eliminating some
simplifying assumptions on its projective equations. A careful experimental
evaluation reveals that the resulting fully projective algorithm has
superexponential convergence properties for a wide range of initial solutions
and, under realistic usage conditions, it is up to an order of magnitude more
accurate than the original formulation, with arguably better computation-time
properties. Our extension to Phong-Horaud's algorithm is, to the best of our
knowledge, the first method for independent orientation recovery that actually
exploits the theoretical advantages of point correspondences over line
correspondences. We show that in the context of a specific real-life application
(visual navigation), it is either more accurate than other similar techniques
with the same computational cost, or more efficient with the same accuracy. }
}