Camera Pose Estimation with Unknown Principal Point

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

Camera Pose Estimation with Unknown Principal Point

Original language description

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.

Czech name

—

Czech description

—

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)

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)

Publication year

2018

Confidentiality

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

Article name in the collection

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

Number of pages

9

Pages from-to

2984-2992

Publisher name

IEEE

Place of publication

Piscataway, NJ

Event location

Salt Lake City

Event date

Jun 19, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000457843603013