Absolute Pose from One or Two Scaled and Oriented Features

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00380114" target="_blank" >RIV/68407700:21230/24:00380114 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21730/24:00380114

Result on the web

<a href="https://doi.org/10.1109/CVPR52733.2024.01972" target="_blank" >https://doi.org/10.1109/CVPR52733.2024.01972</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CVPR52733.2024.01972" target="_blank" >10.1109/CVPR52733.2024.01972</a>

Result language

angličtina

Original language name

Absolute Pose from One or Two Scaled and Oriented Features

Original language description

Keypoints used for image matching often include an estimate of the feature scale and orientation. While recent work has demonstrated the advantages of using feature scales and orientations for relative pose estimation, relatively little work has considered their use for absolute pose estimation. We introduce minimal solutions for absolute pose from two oriented feature correspondences in the general case, or one scaled and oriented correspondence given a known vertical direction. Nowadays, assuming a known direction is not particularly restrictive as modern consumer devices, such as smartphones or drones, are equipped with Inertial Measurement Units (IMU) that provide the gravity direction by default. Compared to traditional absolute pose methods requiring three point correspondences, our solvers need a smaller minimal sample, reducing the cost and complexity of robust estimation. Evaluations on large-scale and public real datasets demonstrate the advantage of our methods for fast and accurate localization in challenging conditions. Code is available at https://github.com/danini/absolute-pose-from-oriented-and-sealed-features.

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/GM22-23183M" target="_blank" >GM22-23183M: New generation of camera geometry solvers</a><br>

Continuities

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

Publication year

2024

Confidentiality

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

Article name in the collection

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

ISBN

979-8-3503-5300-6

ISSN

1063-6919

e-ISSN

2575-7075

Number of pages

11

Pages from-to

20870-20880

Publisher name

IEEE Computer Society

Place of publication

Los Alamitos

Event location

Seattle

Event date

Jun 16, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001342515504022