Radial Distortion Homography

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00235489" target="_blank" >RIV/68407700:21230/15:00235489 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/15:00321165 RIV/68407700:21730/15:00321165

Výsledek na webu

<a href="http://dx.doi.org/10.1109/CVPR.2015.7298663" target="_blank" >http://dx.doi.org/10.1109/CVPR.2015.7298663</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CVPR.2015.7298663" target="_blank" >10.1109/CVPR.2015.7298663</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Radial Distortion Homography

Popis výsledku v původním jazyce

The importance of precise homography estimation is often underestimated even though i t plays a crucial role in various vision applications such as plane or planarity detection, scene degeneracy tests, camera motion classification, image stitching, and many more. Ignoring the rad ial distortion component in homography estimation-even for classical perspective cameras-may lead to significant errors or totally wrong estimates. In this paper, we fill the gap among the homog raphy estimation methods by presenting two algorithms for estimating homography between two camer as with different radial distortions. Both algorithms can handle planar scenes as well as scenes where the relative motion between the cameras is a pure rotation. The first algorithm usesthe mi nimal number of five image point correspondences and solves a nonlinear system of polynomial equa tions using Groebner basis method. The second algorithm uses a non-minimal number of six image poi nt correspondences and leads to a

Název v anglickém jazyce

Radial Distortion Homography

Popis výsledku anglicky

The importance of precise homography estimation is often underestimated even though i t plays a crucial role in various vision applications such as plane or planarity detection, scene degeneracy tests, camera motion classification, image stitching, and many more. Ignoring the rad ial distortion component in homography estimation-even for classical perspective cameras-may lead to significant errors or totally wrong estimates. In this paper, we fill the gap among the homog raphy estimation methods by presenting two algorithms for estimating homography between two camer as with different radial distortions. Both algorithms can handle planar scenes as well as scenes where the relative motion between the cameras is a pure rotation. The first algorithm usesthe mi nimal number of five image point correspondences and solves a nonlinear system of polynomial equa tions using Groebner basis method. The second algorithm uses a non-minimal number of six image poi nt correspondences and leads to a

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

<a href="/cs/project/7E13015" target="_blank" >7E13015: Planetary Robotics Data Exploitation</a><br>

Návaznosti

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

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

CVPR 2015: Proceedings of the 2015 IEEE Computer Society Conference on Computer Vision and Pattern Recognition

ISBN

978-1-4673-6964-0

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

639-647

Název nakladatele

IEEE Computer Society Press

Místo vydání

New York

Místo konání akce

Boston

Datum konání akce

7. 6. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—