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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

  • Czech description

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

    <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

  • 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