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Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset

Monocular cameras and multibeam imaging sonars are common sensors of Unmanned Underwater Vehicles (UUV). In this paper, we propose a new method for calibrating a hybrid sonar–vision system. This method is based on motion comparisons between both images and allows us to compute the transformation mat...

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Detalles Bibliográficos
Autores principales: Pecheux, Nicolas, Creuze, Vincent, Comby, Frédéric, Tempier, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921679/
https://www.ncbi.nlm.nih.gov/pubmed/36772739
http://dx.doi.org/10.3390/s23031700
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author Pecheux, Nicolas
Creuze, Vincent
Comby, Frédéric
Tempier, Olivier
author_facet Pecheux, Nicolas
Creuze, Vincent
Comby, Frédéric
Tempier, Olivier
author_sort Pecheux, Nicolas
collection PubMed
description Monocular cameras and multibeam imaging sonars are common sensors of Unmanned Underwater Vehicles (UUV). In this paper, we propose a new method for calibrating a hybrid sonar–vision system. This method is based on motion comparisons between both images and allows us to compute the transformation matrix between the camera and the sonar and to estimate the camera’s focal length. The main advantage of our method lies in performing the calibration without any specific calibration pattern, while most other existing methods use physical targets. In this paper, we also propose a new sonar–vision dataset and use it to prove the validity of our calibration method.
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spelling pubmed-99216792023-02-12 Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset Pecheux, Nicolas Creuze, Vincent Comby, Frédéric Tempier, Olivier Sensors (Basel) Article Monocular cameras and multibeam imaging sonars are common sensors of Unmanned Underwater Vehicles (UUV). In this paper, we propose a new method for calibrating a hybrid sonar–vision system. This method is based on motion comparisons between both images and allows us to compute the transformation matrix between the camera and the sonar and to estimate the camera’s focal length. The main advantage of our method lies in performing the calibration without any specific calibration pattern, while most other existing methods use physical targets. In this paper, we also propose a new sonar–vision dataset and use it to prove the validity of our calibration method. MDPI 2023-02-03 /pmc/articles/PMC9921679/ /pubmed/36772739 http://dx.doi.org/10.3390/s23031700 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pecheux, Nicolas
Creuze, Vincent
Comby, Frédéric
Tempier, Olivier
Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset
title Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset
title_full Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset
title_fullStr Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset
title_full_unstemmed Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset
title_short Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset
title_sort self calibration of a sonar–vision system for underwater vehicles: a new method and a dataset
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921679/
https://www.ncbi.nlm.nih.gov/pubmed/36772739
http://dx.doi.org/10.3390/s23031700
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