Absolute Pose Estimation from Line Correspondences using Direct Linear Transformation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F17%3APU123657" target="_blank" >RIV/00216305:26230/17:PU123657 - isvavai.cz</a>

Výsledek na webu

<a href="https://authors.elsevier.com/a/1VZpp3qy-3EzCm" target="_blank" >https://authors.elsevier.com/a/1VZpp3qy-3EzCm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cviu.2017.05.002" target="_blank" >10.1016/j.cviu.2017.05.002</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Absolute Pose Estimation from Line Correspondences using Direct Linear Transformation

Popis výsledku v původním jazyce

This work is concerned with camera pose estimation from correspondences of 3D/2D lines, i. e. with the Perspective-n-Line (PnL) problem. We focus on large line sets, which can be efficiently solved by methods using linear formulation of PnL. We propose a novel method "DLT-Combined-Lines" based on the Direct Linear Transformation (DLT) algorithm, which benefits from a new combination of two existing DLT methods for pose estimation. The method represents 2D structure by lines, and 3D structure by both points and lines. The redundant 3D information reduces the minimum required line correspondences to 5. A cornerstone of the method is a combined projection matrix estimated by the DLT algorithm. It contains multiple estimates of camera rotation and translation, which can be recovered after enforcing constraints of the matrix. Multiplicity of the estimates is exploited to improve the accuracy of the proposed method. For large line sets (10 and more), the method is comparable to the state-of-theart in accuracy of orientation estimation. It achieves state-of-the-art accuracy in estimation of camera position and it yields the smallest reprojection error under strong image noise. The method achieves top-3 results on real world data. The proposed method is also highly computationally effective, estimating the pose of 1000 lines in 12 ms on a desktop computer. The Matlab code of the proposed method and the supplementary material is available for download (http://www.fit.vutbr.cz/~ipribyl/DLT-based-PnL/).

Název v anglickém jazyce

Absolute Pose Estimation from Line Correspondences using Direct Linear Transformation

Popis výsledku anglicky

This work is concerned with camera pose estimation from correspondences of 3D/2D lines, i. e. with the Perspective-n-Line (PnL) problem. We focus on large line sets, which can be efficiently solved by methods using linear formulation of PnL. We propose a novel method "DLT-Combined-Lines" based on the Direct Linear Transformation (DLT) algorithm, which benefits from a new combination of two existing DLT methods for pose estimation. The method represents 2D structure by lines, and 3D structure by both points and lines. The redundant 3D information reduces the minimum required line correspondences to 5. A cornerstone of the method is a combined projection matrix estimated by the DLT algorithm. It contains multiple estimates of camera rotation and translation, which can be recovered after enforcing constraints of the matrix. Multiplicity of the estimates is exploited to improve the accuracy of the proposed method. For large line sets (10 and more), the method is comparable to the state-of-theart in accuracy of orientation estimation. It achieves state-of-the-art accuracy in estimation of camera position and it yields the smallest reprojection error under strong image noise. The method achieves top-3 results on real world data. The proposed method is also highly computationally effective, estimating the pose of 1000 lines in 12 ms on a desktop computer. The Matlab code of the proposed method and the supplementary material is available for download (http://www.fit.vutbr.cz/~ipribyl/DLT-based-PnL/).

Druh

J_imp - Článek v periodiku v databázi Web of Science

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/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

COMPUTER VISION AND IMAGE UNDERSTANDING

ISSN

1077-3142

e-ISSN

1090-235X

Svazek periodika

161

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

15

Strana od-do

130-144

Kód UT WoS článku

000410718600012

EID výsledku v databázi Scopus

2-s2.0-85019431048