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Optimal relative pose with unknown correspondences

Fredriksson, Johan LU ; Larsson, Viktor LU ; Olsson, Carl LU and Kahl, Fredrik LU (2016) 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 In 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 2016-January. p.1728-1736
Abstract

Previous work on estimating the epipolar geometry of two views relies on being able to reliably match feature points based on appearance. In this paper, we go one step further and show that it is feasible to compute both the epipolar geometry and the correspondences at the same time based on geometry only. We do this in a globally optimal manner. Our approach is based on an efficient branch and bound technique in combination with bipartite matching to solve the correspondence problem. We rely on several recent works to obtain good bounding functions to battle the combinatorial explosion of possible matchings. It is experimentally demonstrated that more difficult cases can be handled and that more inlier correspondences can be obtained... (More)

Previous work on estimating the epipolar geometry of two views relies on being able to reliably match feature points based on appearance. In this paper, we go one step further and show that it is feasible to compute both the epipolar geometry and the correspondences at the same time based on geometry only. We do this in a globally optimal manner. Our approach is based on an efficient branch and bound technique in combination with bipartite matching to solve the correspondence problem. We rely on several recent works to obtain good bounding functions to battle the combinatorial explosion of possible matchings. It is experimentally demonstrated that more difficult cases can be handled and that more inlier correspondences can be obtained by being less restrictive in the matching phase.

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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
volume
2016-January
pages
9 pages
publisher
IEEE Computer Society
conference name
2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
external identifiers
  • scopus:84986309859
ISBN
9781467388511
language
English
LU publication?
yes
id
d924add7-bc8e-4755-9adc-3491b52387b7
date added to LUP
2017-02-17 08:03:21
date last changed
2017-02-17 08:03:21
@inproceedings{d924add7-bc8e-4755-9adc-3491b52387b7,
  abstract     = {<p>Previous work on estimating the epipolar geometry of two views relies on being able to reliably match feature points based on appearance. In this paper, we go one step further and show that it is feasible to compute both the epipolar geometry and the correspondences at the same time based on geometry only. We do this in a globally optimal manner. Our approach is based on an efficient branch and bound technique in combination with bipartite matching to solve the correspondence problem. We rely on several recent works to obtain good bounding functions to battle the combinatorial explosion of possible matchings. It is experimentally demonstrated that more difficult cases can be handled and that more inlier correspondences can be obtained by being less restrictive in the matching phase.</p>},
  author       = {Fredriksson, Johan and Larsson, Viktor and Olsson, Carl and Kahl, Fredrik},
  booktitle    = {2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016},
  isbn         = {9781467388511},
  language     = {eng},
  pages        = {1728--1736},
  publisher    = {IEEE Computer Society},
  title        = {Optimal relative pose with unknown correspondences},
  volume       = {2016-January},
  year         = {2016},
}