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Radial Distortion Triangulation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00335893" target="_blank" >RIV/68407700:21230/19:00335893 - isvavai.cz</a>

  • Result on the web

    <a href="http://openaccess.thecvf.com/content_CVPR_2019/html/Kukelova_Radial_Distortion_Triangulation_CVPR_2019_paper.html" target="_blank" >http://openaccess.thecvf.com/content_CVPR_2019/html/Kukelova_Radial_Distortion_Triangulation_CVPR_2019_paper.html</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/CVPR.2019.00991" target="_blank" >10.1109/CVPR.2019.00991</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Radial Distortion Triangulation

  • Original language description

    This paper presents the first optimal, maximal likelihood, solution to the triangulation problem for radially distorted cameras. The proposed solution to the two-view triangulation problem minimizes the L2-norm of the reprojection error in the distorted image space. We cast the problem as the search for corrected distorted image points, and we use a Lagrange multiplier formulation to impose the epipolar constraint for undistorted points. For the one-parameter division model, this formulation leads to a system of five quartic polynomial equations in five unknowns, which can be exactly solved using the Groebner basis method. While the proposed Groebner basis solution is provably optimal; it is too slow for practical applications. Therefore, we developed a fast iterative solver to this problem. Extensive empirical tests show that the iterative algorithm delivers the optimal solution virtually every time, thus making it an L2-optimal algorithm de facto. It is iterative in nature, yet in practice, it converges in no more than five iterations. We thoroughly evaluate the proposed method on both synthetic and real-world data, and we show the benefits of performing the triangulation in the distorted space in the presence of radial distortion.

  • 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/EF17_050%2F0008025" target="_blank" >EF17_050/0008025: International Mobility of Researchers ? MSCA-IF in CTU</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • 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 2019: Proceedings of the 2019 IEEE Conference on Computer Vision and Pattern Recognition

  • ISBN

    978-1-7281-3293-8

  • ISSN

    1063-6919

  • e-ISSN

    2575-7075

  • Number of pages

    9

  • Pages from-to

    9673-9681

  • Publisher name

    IEEE

  • Place of publication

  • Event location

    Long Beach

  • Event date

    Jun 15, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article