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Are Minimal Radial Distortion Solvers Necessary for Relative Pose Estimation?

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00377191" target="_blank" >RIV/68407700:21230/25:00377191 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21730/25:00377191

  • Result on the web

    <a href="https://doi.org/10.1007/978-3-031-91569-7_7" target="_blank" >https://doi.org/10.1007/978-3-031-91569-7_7</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-91569-7_7" target="_blank" >10.1007/978-3-031-91569-7_7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Are Minimal Radial Distortion Solvers Necessary for Relative Pose Estimation?

  • Original language description

    Estimating the relative pose between two cameras is a fundamental step in many applications such as Structure-from-Motion. The common approach to relative pose estimation is to apply a minimal solver inside a RANSAC loop. Highly efficient solvers exist for pinhole cameras. Yet, (nearly) all cameras exhibit radial distortion. Not modeling radial distortion leads to (significantly) worse results. However, minimal radial distortion solvers are significantly more complex than pinhole solvers, both in terms of run-time and implementation efforts. This paper compares radial distortion solvers with a simple-to-implement baseline that combines an efficient pinhole solver with sampled radial distortion parameters. Extensive experiments on multiple datasets and RANSAC variants show that this simple baseline performs similarly or better than the most accurate minimal distortion solvers at faster run-times while being significantly more accurate than faster non-minimal solvers. Our results clearly show that complex radial distortion solvers are not necessary in practice. We will make the code and a new benchmark available.

  • 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/GM22-23183M" target="_blank" >GM22-23183M: New generation of camera geometry solvers</a><br>

  • Continuities

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

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    ECCV 2024 Workshops - Half-Century of Structure-from-Motion

  • ISBN

    978-3-031-91568-0

  • ISSN

    0302-9743

  • e-ISSN

    1611-3349

  • Number of pages

    17

  • Pages from-to

    91-107

  • Publisher name

    Springer Nature Switzerland AG

  • Place of publication

    Cham

  • Event location

    Milano

  • Event date

    Sep 29, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001544976800007