3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/LAGIRS48042.2020.9165687 http://hdl.handle.net/11449/206572 |
Resumo: | This paper presents a feasibility study on the use of omnidirectional systems for 3D modelling of agricultural crops, aiming a systematic monitoring. Omnidirectional systems with multiple sensors have been widely used in close-range photogrammetry (CRP), which can be a good alternative to provide data for digital agriculture management. The GoPro Fusion dual-camera is the omnidirectional system used in this work. This system is composed of two cameras with fisheye lenses that cover more than 180° each one in back-to-back position. System calibration, camera orientation and 3D reconstruction of an agricultural cultivated area were performed in Agisoft Metashape software. A 360° calibration field based on coded targets (CTs) from Agisoft Metashape software was used to calibrate the omnidirectional system. The 3D reconstruction of an orange orchard was performed using fisheye images taken with GoPro Fusion. The results show the potential of using an omnidirectional system for 3D modelling in agricultural crops, in particular citrus trees. Interior orientation parameters (IOPs) was estimated using Agisoft Metashape target/software with a precision of 9 mm. A 3D reconstruction model of the orange orchard area was obtained with an accuracy of 3.8 cm, which can be considered acceptable for agricultural purposes. |
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3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System3D tree modellingcamera calibrationDigital agriculturedual-camerafisheye lensorange orchardpoly-dioptric systemterrestrial mappingThis paper presents a feasibility study on the use of omnidirectional systems for 3D modelling of agricultural crops, aiming a systematic monitoring. Omnidirectional systems with multiple sensors have been widely used in close-range photogrammetry (CRP), which can be a good alternative to provide data for digital agriculture management. The GoPro Fusion dual-camera is the omnidirectional system used in this work. This system is composed of two cameras with fisheye lenses that cover more than 180° each one in back-to-back position. System calibration, camera orientation and 3D reconstruction of an agricultural cultivated area were performed in Agisoft Metashape software. A 360° calibration field based on coded targets (CTs) from Agisoft Metashape software was used to calibrate the omnidirectional system. The 3D reconstruction of an orange orchard was performed using fisheye images taken with GoPro Fusion. The results show the potential of using an omnidirectional system for 3D modelling in agricultural crops, in particular citrus trees. Interior orientation parameters (IOPs) was estimated using Agisoft Metashape target/software with a precision of 9 mm. A 3D reconstruction model of the orange orchard area was obtained with an accuracy of 3.8 cm, which can be considered acceptable for agricultural purposes.São Paulo State University (UNESP) at Presidente Prudente Department of CartographyFinnish Geospatial Research Institute FGI Department of Remote Sensing and Photogrammetry, Geodeetinrinne 2São Paulo State University (UNESP) at Presidente Prudente Department of CartographyUniversidade Estadual Paulista (Unesp)Finnish Geospatial Research Institute FGICastanheiro, L. F. [UNESP]Tommaselli, A. M.G. [UNESP]Campos, M. B.Berveglieri, A. [UNESP]Santos, G. [UNESP]2021-06-25T10:34:30Z2021-06-25T10:34:30Z2020-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject409-414http://dx.doi.org/10.1109/LAGIRS48042.2020.91656872020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 - Proceedings, p. 409-414.http://hdl.handle.net/11449/20657210.1109/LAGIRS48042.2020.91656872-s2.0-85091655022Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 - Proceedingsinfo:eu-repo/semantics/openAccess2021-10-23T07:34:09Zoai:repositorio.unesp.br:11449/206572Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T07:34:09Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System |
title |
3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System |
spellingShingle |
3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System Castanheiro, L. F. [UNESP] 3D tree modelling camera calibration Digital agriculture dual-camera fisheye lens orange orchard poly-dioptric system terrestrial mapping |
title_short |
3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System |
title_full |
3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System |
title_fullStr |
3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System |
title_full_unstemmed |
3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System |
title_sort |
3D Reconstruction of Citrus Trees Using an Omnidirectional Optical System |
author |
Castanheiro, L. F. [UNESP] |
author_facet |
Castanheiro, L. F. [UNESP] Tommaselli, A. M.G. [UNESP] Campos, M. B. Berveglieri, A. [UNESP] Santos, G. [UNESP] |
author_role |
author |
author2 |
Tommaselli, A. M.G. [UNESP] Campos, M. B. Berveglieri, A. [UNESP] Santos, G. [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Finnish Geospatial Research Institute FGI |
dc.contributor.author.fl_str_mv |
Castanheiro, L. F. [UNESP] Tommaselli, A. M.G. [UNESP] Campos, M. B. Berveglieri, A. [UNESP] Santos, G. [UNESP] |
dc.subject.por.fl_str_mv |
3D tree modelling camera calibration Digital agriculture dual-camera fisheye lens orange orchard poly-dioptric system terrestrial mapping |
topic |
3D tree modelling camera calibration Digital agriculture dual-camera fisheye lens orange orchard poly-dioptric system terrestrial mapping |
description |
This paper presents a feasibility study on the use of omnidirectional systems for 3D modelling of agricultural crops, aiming a systematic monitoring. Omnidirectional systems with multiple sensors have been widely used in close-range photogrammetry (CRP), which can be a good alternative to provide data for digital agriculture management. The GoPro Fusion dual-camera is the omnidirectional system used in this work. This system is composed of two cameras with fisheye lenses that cover more than 180° each one in back-to-back position. System calibration, camera orientation and 3D reconstruction of an agricultural cultivated area were performed in Agisoft Metashape software. A 360° calibration field based on coded targets (CTs) from Agisoft Metashape software was used to calibrate the omnidirectional system. The 3D reconstruction of an orange orchard was performed using fisheye images taken with GoPro Fusion. The results show the potential of using an omnidirectional system for 3D modelling in agricultural crops, in particular citrus trees. Interior orientation parameters (IOPs) was estimated using Agisoft Metashape target/software with a precision of 9 mm. A 3D reconstruction model of the orange orchard area was obtained with an accuracy of 3.8 cm, which can be considered acceptable for agricultural purposes. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-03-01 2021-06-25T10:34:30Z 2021-06-25T10:34:30Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/LAGIRS48042.2020.9165687 2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 - Proceedings, p. 409-414. http://hdl.handle.net/11449/206572 10.1109/LAGIRS48042.2020.9165687 2-s2.0-85091655022 |
url |
http://dx.doi.org/10.1109/LAGIRS48042.2020.9165687 http://hdl.handle.net/11449/206572 |
identifier_str_mv |
2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 - Proceedings, p. 409-414. 10.1109/LAGIRS48042.2020.9165687 2-s2.0-85091655022 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 - Proceedings |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
409-414 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1799965053707878400 |