Camera Pose Estimation with Unknown Principal Point

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00326730" target="_blank" >RIV/68407700:21230/18:00326730 - isvavai.cz</a>

Výsledek na webu

<a href="http://openaccess.thecvf.com/content_cvpr_2018/html/Larsson_Camera_Pose_Estimation_CVPR_2018_paper.html" target="_blank" >http://openaccess.thecvf.com/content_cvpr_2018/html/Larsson_Camera_Pose_Estimation_CVPR_2018_paper.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CVPR.2018.00315" target="_blank" >10.1109/CVPR.2018.00315</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Camera Pose Estimation with Unknown Principal Point

Popis výsledku v původním jazyce

To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization. In most of existing camera pose estimation solvers, the principal point is assumed to be in the image center. Unfortunately, this assumption is not always true, especially for asymmetrically cropped images. In this paper, we develop the first exactly minimal solver for the case of unknown principal point and focal length by using four and a half point correspondences (P4.5Pfuv). We also present an extremely fast solver for the case of unknown aspect ratio (P5Pfuva). The new solvers outperform the previous state-of-the-art in terms of stability and speed. Finally, we explore the extremely challenging case of both unknown principal point and radial distortion, and develop the first practical non-minimal solver by using seven point correspondences (P7Pfruv). Experimental results on both simulated data and real Internet images demonstrate the usefulness of our new solvers.

Název v anglickém jazyce

Camera Pose Estimation with Unknown Principal Point

Popis výsledku anglicky

To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization. In most of existing camera pose estimation solvers, the principal point is assumed to be in the image center. Unfortunately, this assumption is not always true, especially for asymmetrically cropped images. In this paper, we develop the first exactly minimal solver for the case of unknown principal point and focal length by using four and a half point correspondences (P4.5Pfuv). We also present an extremely fast solver for the case of unknown aspect ratio (P5Pfuva). The new solvers outperform the previous state-of-the-art in terms of stability and speed. Finally, we explore the extremely challenging case of both unknown principal point and radial distortion, and develop the first practical non-minimal solver by using seven point correspondences (P7Pfruv). Experimental results on both simulated data and real Internet images demonstrate the usefulness of our new solvers.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/project/EF17_050%2F0008025" target="_blank" >EF17_050/0008025: Mezinárodní mobility výzkumných pracovníků MSCA-IF na ČVUT</a><br>

Návaznosti

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

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition

ISBN

978-1-5386-6420-9

ISSN

1063-6919

e-ISSN

2575-7075

Počet stran výsledku

9

Strana od-do

2984-2992

Název nakladatele

IEEE

Místo vydání

Piscataway, NJ

Místo konání akce

Salt Lake City

Datum konání akce

19. 6. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000457843603013