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Efficient Minimal Solvers for Relative Pose Estimation With Known Rotation Angle

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00388101" target="_blank" >RIV/68407700:21230/25:00388101 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.1109/LRA.2025.3585382" target="_blank" >https://doi.org/10.1109/LRA.2025.3585382</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/LRA.2025.3585382" target="_blank" >10.1109/LRA.2025.3585382</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Efficient Minimal Solvers for Relative Pose Estimation With Known Rotation Angle

  • Popis výsledku v původním jazyce

    In this letter, we propose novel minimal solvers for calibrated relative pose estimation with a known rotation angle. This scenario is particularly relevant for devices such as smartphones, tablets, and camera-IMU (Inertial Measurement Unit) systems, where gyroscopes provide precise measurements of the rotation angle. By leveraging the prior knowledge of the rotation angle from the gyroscope, the relative rotation between two views can be reduced to 2 degrees of freedom (DOF), and the relative pose estimation problem is simplified to 4-DOF. This reduction enables the estimation of the relative pose using only four-point correspondences. Unlike previous approaches, we address both cases where the four points are in general positions or coplanar. For points in general positions, we present a straightforward yet effective method to eliminate specific monomials in the equations, leading to a more computationally efficient solution. For coplanar points, we establish a connection between the homography matrix and the essential matrix, introducing new constraints on the homography matrix. Based on these constraints, we derive a new solver for homography-based relative pose estimation with a known rotation angle. We provide comprehensive analyses and comparisons against state-of-the-art algorithms, demonstrating the superior efficiency and effectiveness of our proposed method. Our results highlight the practical applicability of our solvers in real-world scenarios, particularly for devices equipped with IMUs.

  • Název v anglickém jazyce

    Efficient Minimal Solvers for Relative Pose Estimation With Known Rotation Angle

  • Popis výsledku anglicky

    In this letter, we propose novel minimal solvers for calibrated relative pose estimation with a known rotation angle. This scenario is particularly relevant for devices such as smartphones, tablets, and camera-IMU (Inertial Measurement Unit) systems, where gyroscopes provide precise measurements of the rotation angle. By leveraging the prior knowledge of the rotation angle from the gyroscope, the relative rotation between two views can be reduced to 2 degrees of freedom (DOF), and the relative pose estimation problem is simplified to 4-DOF. This reduction enables the estimation of the relative pose using only four-point correspondences. Unlike previous approaches, we address both cases where the four points are in general positions or coplanar. For points in general positions, we present a straightforward yet effective method to eliminate specific monomials in the equations, leading to a more computationally efficient solution. For coplanar points, we establish a connection between the homography matrix and the essential matrix, introducing new constraints on the homography matrix. Based on these constraints, we derive a new solver for homography-based relative pose estimation with a known rotation angle. We provide comprehensive analyses and comparisons against state-of-the-art algorithms, demonstrating the superior efficiency and effectiveness of our proposed method. Our results highlight the practical applicability of our solvers in real-world scenarios, particularly for devices equipped with IMUs.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/GM22-23183M" target="_blank" >GM22-23183M: Nová generace algoritmů pro řešení problémů geometrie kamer</a><br>

  • Návaznosti

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

Ostatní

  • Rok uplatnění

    2025

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název periodika

    IEEE Robotics and Automation Letters

  • ISSN

    2377-3766

  • e-ISSN

    2377-3766

  • Svazek periodika

    10

  • Číslo periodika v rámci svazku

    8

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    7

  • Strana od-do

    8404-8410

  • Kód UT WoS článku

    001527211400007

  • EID výsledku v databázi Scopus

    2-s2.0-105010357919