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PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features
To address the problem of estimating camera trajectory and to build a structural three-dimensional (3D) map based on inertial measurements and visual observations, this paper proposes point–line visual–inertial odometry (PL-VIO), a tightly-coupled monocular visual–inertial odometry system exploiting...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948686/ https://www.ncbi.nlm.nih.gov/pubmed/29642648 http://dx.doi.org/10.3390/s18041159 |
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author | He, Yijia Zhao, Ji Guo, Yue He, Wenhao Yuan, Kui |
author_facet | He, Yijia Zhao, Ji Guo, Yue He, Wenhao Yuan, Kui |
author_sort | He, Yijia |
collection | PubMed |
description | To address the problem of estimating camera trajectory and to build a structural three-dimensional (3D) map based on inertial measurements and visual observations, this paper proposes point–line visual–inertial odometry (PL-VIO), a tightly-coupled monocular visual–inertial odometry system exploiting both point and line features. Compared with point features, lines provide significantly more geometrical structure information on the environment. To obtain both computation simplicity and representational compactness of a 3D spatial line, Plücker coordinates and orthonormal representation for the line are employed. To tightly and efficiently fuse the information from inertial measurement units (IMUs) and visual sensors, we optimize the states by minimizing a cost function which combines the pre-integrated IMU error term together with the point and line re-projection error terms in a sliding window optimization framework. The experiments evaluated on public datasets demonstrate that the PL-VIO method that combines point and line features outperforms several state-of-the-art VIO systems which use point features only. |
format | Online Article Text |
id | pubmed-5948686 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-59486862018-05-17 PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features He, Yijia Zhao, Ji Guo, Yue He, Wenhao Yuan, Kui Sensors (Basel) Article To address the problem of estimating camera trajectory and to build a structural three-dimensional (3D) map based on inertial measurements and visual observations, this paper proposes point–line visual–inertial odometry (PL-VIO), a tightly-coupled monocular visual–inertial odometry system exploiting both point and line features. Compared with point features, lines provide significantly more geometrical structure information on the environment. To obtain both computation simplicity and representational compactness of a 3D spatial line, Plücker coordinates and orthonormal representation for the line are employed. To tightly and efficiently fuse the information from inertial measurement units (IMUs) and visual sensors, we optimize the states by minimizing a cost function which combines the pre-integrated IMU error term together with the point and line re-projection error terms in a sliding window optimization framework. The experiments evaluated on public datasets demonstrate that the PL-VIO method that combines point and line features outperforms several state-of-the-art VIO systems which use point features only. MDPI 2018-04-10 /pmc/articles/PMC5948686/ /pubmed/29642648 http://dx.doi.org/10.3390/s18041159 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article He, Yijia Zhao, Ji Guo, Yue He, Wenhao Yuan, Kui PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features |
title | PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features |
title_full | PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features |
title_fullStr | PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features |
title_full_unstemmed | PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features |
title_short | PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features |
title_sort | pl-vio: tightly-coupled monocular visual–inertial odometry using point and line features |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948686/ https://www.ncbi.nlm.nih.gov/pubmed/29642648 http://dx.doi.org/10.3390/s18041159 |
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