P1AC: Revisiting Absolute Pose From a Single Affine Correspondence

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00372033" target="_blank" >RIV/68407700:21230/23:00372033 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21730/23:00372033

Result on the web

<a href="https://doi.org/10.1109/ICCV51070.2023.01809" target="_blank" >https://doi.org/10.1109/ICCV51070.2023.01809</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICCV51070.2023.01809" target="_blank" >10.1109/ICCV51070.2023.01809</a>

Result language

angličtina

Original language name

P1AC: Revisiting Absolute Pose From a Single Affine Correspondence

Original language description

Affine correspondences have traditionally been used to improve feature matching over wide baselines. While recent work has successfully used affine correspondences to solve various relative camera pose estimation problems, less attention has been given to their use in absolute pose estimation. We introduce the first general solution to the problem of estimating the pose of a calibrated camera given a single observation of an oriented point and an affine correspondence. The advantage of our approach (P1AC) is that it requires only a single correspondence, in compar ison to the traditional point-based approach (P3P), significantly reducing the combinatorics in robust estimation. P1AC provides a general solution that removes restrictive assumptions made in prior work and is applicable to large-scale image-based localization. We propose a minimal solution to the P1AC problem and evaluate our novel solver on synthetic data, showing its numerical stability and performance under various types of noise. On standard image-based localization benchmarks we show that P1AC achieves more accurate results than the widely used P3P algorithm. Code for our method is available at https: //github.com/jonathanventura/P1AC/

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

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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

Publication year

2023

Confidentiality

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

Article name in the collection

ICCV2023: Proceedings of the International Conference on Computer Vision

ISBN

979-8-3503-0719-1

ISSN

1550-5499

e-ISSN

2380-7504

Number of pages

11

Pages from-to

19694-19704

Publisher name

IEEE

Place of publication

Piscataway

Event location

Paris

Event date

Oct 2, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001169500504030