A QCQP Approach to Triangulation
Optimization and Control
2012-08-09 v2
Abstract
Triangulation of a three-dimensional point from at least two noisy 2-D images can be formulated as a quadratically constrained quadratic program. We propose an algorithm to extract candidate solutions to this problem from its semidefinite programming relaxations. We then describe a sufficient condition and a polynomial time test for certifying when such a solution is optimal. This test has no false positives. Experiments indicate that false negatives are rare, and the algorithm has excellent performance in practice. We explain this phenomenon in terms of the geometry of the triangulation problem.
Cite
@article{arxiv.1207.7160,
title = {A QCQP Approach to Triangulation},
author = {Chris Aholt and Sameer Agarwal and Rekha Thomas},
journal= {arXiv preprint arXiv:1207.7160},
year = {2012}
}
Comments
14 pages, to appear in the proceedings of the 12th European Conference of Computer Vision, Firenze, Italy, 7-13 October 2012