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Efficient Solvers for Minimal Problems by Syzygy-based Reduction

Larsson, Viktor LU ; Åström, Karl LU and Oskarsson, Magnus LU (2017) IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 p.2383-2392
Abstract
In this paper we study the problem of automatically generating
polynomial solvers for minimal problems. The main
contribution is a new method for finding small elimination
templates by making use of the syzygies (i.e. the polynomial
relations) that exist between the original equations. Using
these syzygies we can essentially parameterize the set
of possible elimination templates.
We evaluate our method on a wide variety of problems
from geometric computer vision and show improvement
compared to both handcrafted and automatically generated
solvers. Furthermore we apply our method on two previously
unsolved relative orientation problems.
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
host publication
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
pages
10 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
conference location
Honolulu, United States
conference dates
2017-07-21 - 2017-07-26
external identifiers
  • scopus:85041930337
ISBN
978-1-5386-0458-8
978-1-5386-0457-1
DOI
10.1109/CVPR.2017.256
language
English
LU publication?
yes
id
e10f7381-3eeb-43e8-b138-5c3f8c2cde74
alternative location
http://openaccess.thecvf.com/content_cvpr_2017/papers/Larsson_Efficient_Solvers_for_CVPR_2017_paper.pdf
date added to LUP
2018-01-26 22:43:34
date last changed
2019-02-03 05:29:58
@inproceedings{e10f7381-3eeb-43e8-b138-5c3f8c2cde74,
  abstract     = {In this paper we study the problem of automatically generating<br/>polynomial solvers for minimal problems. The main<br/>contribution is a new method for finding small elimination<br/>templates by making use of the syzygies (i.e. the polynomial<br/>relations) that exist between the original equations. Using<br/>these syzygies we can essentially parameterize the set<br/>of possible elimination templates.<br/>We evaluate our method on a wide variety of problems<br/>from geometric computer vision and show improvement<br/>compared to both handcrafted and automatically generated<br/>solvers. Furthermore we apply our method on two previously<br/>unsolved relative orientation problems.},
  author       = {Larsson, Viktor and Åström, Karl and Oskarsson, Magnus},
  isbn         = {978-1-5386-0458-8 },
  language     = {eng},
  location     = {Honolulu, United States},
  pages        = {2383--2392},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Efficient Solvers for Minimal Problems by Syzygy-based Reduction},
  url          = {http://dx.doi.org/10.1109/CVPR.2017.256},
  year         = {2017},
}