A clever elimination strategy for efficient minimal solvers

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>

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

—

Czech description

—

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)

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)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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

—

Number of pages

10

Pages from-to

3605-3614

Publisher name

IEEE Computer Society Press

Place of publication

—

Event location

Honolulu

Event date

Jul 21, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000418371403073