Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

The registration problem revisited: Optimal solutions from points, lines and planes

Olsson, Carl LU ; Kahl, Fredrik LU and Oskarsson, Magnus LU (2006) 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 1. p.1206-1213
Abstract
In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework that allows us to use both point-to-point, point-to-line and point-to-plane correspondences in the optimization algorithm. Traditional methods such as the iterative closest point algorithm may get trapped in local minima due to the non-convexity of the problem, however, our approach guarantees global optimality. The approach is based on ideas from global optimization theory, in particular, convex under-estimators in combination with branch and bound. We provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data.
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Under-estimators, Non-convexity, Point-to-line, Point-to-plane
host publication
Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
volume
1
pages
1206 - 1213
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
conference location
New York, NY, United States
conference dates
2006-06-17 - 2006-06-22
external identifiers
  • scopus:33845572537
DOI
10.1109/CVPR.2006.307
language
English
LU publication?
yes
id
afaceff1-a2e1-4c07-9b0c-19d14e9032dd (old id 616690)
date added to LUP
2016-04-04 10:21:28
date last changed
2021-04-13 03:56:16
@inproceedings{afaceff1-a2e1-4c07-9b0c-19d14e9032dd,
  abstract     = {In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework that allows us to use both point-to-point, point-to-line and point-to-plane correspondences in the optimization algorithm. Traditional methods such as the iterative closest point algorithm may get trapped in local minima due to the non-convexity of the problem, however, our approach guarantees global optimality. The approach is based on ideas from global optimization theory, in particular, convex under-estimators in combination with branch and bound. We provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data.},
  author       = {Olsson, Carl and Kahl, Fredrik and Oskarsson, Magnus},
  booktitle    = {Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006},
  language     = {eng},
  pages        = {1206--1213},
  publisher    = {IEEE - Institute of Electrical and Electronics Engineers Inc.},
  title        = {The registration problem revisited: Optimal solutions from points, lines and planes},
  url          = {http://dx.doi.org/10.1109/CVPR.2006.307},
  doi          = {10.1109/CVPR.2006.307},
  volume       = {1},
  year         = {2006},
}