Beyond Gröbner Bases: Basis Selection for Minimal Solvers
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00327278" target="_blank" >RIV/68407700:21230/18:00327278 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/18:00327278
Result on the web
<a href="http://openaccess.thecvf.com/content_cvpr_2018/papers_backup/Larsson_Beyond_GroBner_Bases_CVPR_2018_paper.pdf" target="_blank" >http://openaccess.thecvf.com/content_cvpr_2018/papers_backup/Larsson_Beyond_GroBner_Bases_CVPR_2018_paper.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR.2018.00415" target="_blank" >10.1109/CVPR.2018.00415</a>
Alternative languages
Result language
angličtina
Original language name
Beyond Gröbner Bases: Basis Selection for Minimal Solvers
Original language description
Many computer vision applications require robust estimation of the underlying geometry, in terms of camera motion and 3D structure of the scene. These robust methods often rely on running minimal solvers in a RANSAC framework. In this paper we show how we can make polynomial solvers based on the action matrix method faster, by careful selection of the monomial bases. These monomial bases have traditionally been based on a Gröbner basis for the polynomial ideal. Here we describe how we can enumerate all such bases in an efficient way. We also show that going beyond Gröbner bases leads to more efficient solvers in many cases. We present a novel basis sampling scheme that we evaluate on a number of problems
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition
ISBN
978-1-5386-6420-9
ISSN
1063-6919
e-ISSN
2575-7075
Number of pages
10
Pages from-to
3945-3954
Publisher name
IEEE
Place of publication
Piscataway, NJ
Event location
Salt Lake City
Event date
Jun 19, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000457843604010