Advanced

Solving Quadratically Constrained Geometrical Problems using Lagrangian Duality

Olsson, Carl LU and Eriksson, Anders P LU (2008) 19th International Conference on Pattern Recognition (ICPR 2008) In 19th International Conference on Pattern Recognition, 2008. ICPR 2008. p.2469-2473
Abstract
In this paper we consider the problem of solving different pose and registration problems under rotational constraints. Traditionally, methods such as the iterative closest point algorithm have been used to solve these problems. They may however get stuck in local minima due to the non-convexity of the problem. In recent years methods for finding the global optimum, based on Branch and Bound and convex under-estimators, have been developed. These methods are provably optimal, however since they are based on global optimization methods they are in general more time consuming than local methods. In this paper we adopt a dual approach. Rather than trying to find the globally optimal solution we investigate the quality of the solutions... (More)
In this paper we consider the problem of solving different pose and registration problems under rotational constraints. Traditionally, methods such as the iterative closest point algorithm have been used to solve these problems. They may however get stuck in local minima due to the non-convexity of the problem. In recent years methods for finding the global optimum, based on Branch and Bound and convex under-estimators, have been developed. These methods are provably optimal, however since they are based on global optimization methods they are in general more time consuming than local methods. In this paper we adopt a dual approach. Rather than trying to find the globally optimal solution we investigate the quality of the solutions obtained using Lagrange duality. Our approach allows its to formulate a single convex semidefinite program that approximates the original problem well. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
19th International Conference on Pattern Recognition, 2008. ICPR 2008.
pages
2469 - 2473
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
19th International Conference on Pattern Recognition (ICPR 2008)
external identifiers
  • wos:000264729001123
  • scopus:77957935298
ISSN
1051-4651
ISBN
978-1-4244-2174-9
DOI
10.1109/ICPR.2008.4761896
language
English
LU publication?
yes
id
313a561a-c5b5-4cce-953a-17899c83711e (old id 1399321)
date added to LUP
2009-05-28 12:45:40
date last changed
2017-01-01 05:55:59
@inproceedings{313a561a-c5b5-4cce-953a-17899c83711e,
  abstract     = {In this paper we consider the problem of solving different pose and registration problems under rotational constraints. Traditionally, methods such as the iterative closest point algorithm have been used to solve these problems. They may however get stuck in local minima due to the non-convexity of the problem. In recent years methods for finding the global optimum, based on Branch and Bound and convex under-estimators, have been developed. These methods are provably optimal, however since they are based on global optimization methods they are in general more time consuming than local methods. In this paper we adopt a dual approach. Rather than trying to find the globally optimal solution we investigate the quality of the solutions obtained using Lagrange duality. Our approach allows its to formulate a single convex semidefinite program that approximates the original problem well.},
  author       = {Olsson, Carl and Eriksson, Anders P},
  booktitle    = {19th International Conference on Pattern Recognition, 2008. ICPR 2008.},
  isbn         = {978-1-4244-2174-9},
  issn         = {1051-4651},
  language     = {eng},
  pages        = {2469--2473},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Solving Quadratically Constrained Geometrical Problems using Lagrangian Duality},
  url          = {http://dx.doi.org/10.1109/ICPR.2008.4761896},
  year         = {2008},
}