A clever elimination strategy for efficient minimal solvers
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315124" target="_blank" >RIV/68407700:21230/17:00315124 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/17:00315124
Result on the web
<a href="http://openaccess.thecvf.com/content_cvpr_2017/papers/Kukelova_A_Clever_Elimination_CVPR_2017_paper.pdf" target="_blank" >http://openaccess.thecvf.com/content_cvpr_2017/papers/Kukelova_A_Clever_Elimination_CVPR_2017_paper.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR.2017.384" target="_blank" >10.1109/CVPR.2017.384</a>
Alternative languages
Result language
angličtina
Original language name
A clever elimination strategy for efficient minimal solvers
Original language description
We present a new insight into the systematic generation of minimal solvers in computer vision, which leads to smaller and faster solvers. Many minimal problem formulations are coupled sets of linear and polynomial equations where image measurements enter the linear equations only. We show that it is useful to solve such systems by first eliminating all the unknowns that do not appear in the linear equations and then extending solutions to the rest of unknowns. This can be generalized to fully non-linear systems by linearization via lifting. We demonstrate that this approach leads to more efficient solvers in three problems of partially calibrated relative camera pose computation with unknown focal length and/or radial distortion. Our approach also generates new interesting constraints on the fundamental matrices of partially calibrated cameras, which were not known before.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
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 2017: Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition
ISBN
978-1-5386-0457-1
ISSN
1063-6919
e-ISSN
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Number of pages
10
Pages from-to
3605-3614
Publisher name
IEEE Computer Society Press
Place of publication
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Event location
Honolulu
Event date
Jul 21, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000418371403073