3D reconstruction of building model using UAV point clouds
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Idioma: | eng |
Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Texto Completo: | https://hdl.handle.net/1822/89222 |
Resumo: | Photo-realistic 3D model of object cannot be created by using conventional Total Station method. The aim of this study is to generate 3D building model using UAV's dense point clouds. In this research, the ability of remotely detected information for the construction of 3D building models is found to be as specific as UAV datasets, Tacheometry Survey and Traverse Survey. Pix4D and MeshLab software were used in this study to perform image processing of 3D building. The building was built up upon using the information needed from capturing UAV images. This procedure requires the height of building to be measured through conventional method such that of UAV and the height is then compared with a 3D building model. At the end of the process, the comparison of height of building, also known as RMSE, was conducted. The images of building were then processed in Photogrammetry which is the Pix4D software. Using Pix4D, this study proceeded with several processing stages such as camera calibration, photo uploading, building of dense cloud, mesh generation, and model texturing. Those processes were done automatically by using Pix4D tools. High quality of photo-realistic 3D model of building was then successfully constructed. The accuracy assessment was done by comparing the measurement of 3D model of building. Direct measuring of building by using total station had taken place to compare the measurements between 3D model details with actual measurements. The measurement of 3D model of building was done in Pix4D software. The RMSE achieved in this study is 0.015 m which is under reasonable accuracy limit. This study proves that UAV point cloud is capable to produce a very fine 3D model. |
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spelling |
3D reconstruction of building model using UAV point clouds3D modelPoint cloudPrecisionUAVScience & TechnologyPhoto-realistic 3D model of object cannot be created by using conventional Total Station method. The aim of this study is to generate 3D building model using UAV's dense point clouds. In this research, the ability of remotely detected information for the construction of 3D building models is found to be as specific as UAV datasets, Tacheometry Survey and Traverse Survey. Pix4D and MeshLab software were used in this study to perform image processing of 3D building. The building was built up upon using the information needed from capturing UAV images. This procedure requires the height of building to be measured through conventional method such that of UAV and the height is then compared with a 3D building model. At the end of the process, the comparison of height of building, also known as RMSE, was conducted. The images of building were then processed in Photogrammetry which is the Pix4D software. Using Pix4D, this study proceeded with several processing stages such as camera calibration, photo uploading, building of dense cloud, mesh generation, and model texturing. Those processes were done automatically by using Pix4D tools. High quality of photo-realistic 3D model of building was then successfully constructed. The accuracy assessment was done by comparing the measurement of 3D model of building. Direct measuring of building by using total station had taken place to compare the measurements between 3D model details with actual measurements. The measurement of 3D model of building was done in Pix4D software. The RMSE achieved in this study is 0.015 m which is under reasonable accuracy limit. This study proves that UAV point cloud is capable to produce a very fine 3D model.Faculty of Architecture, Planning, and Surveying Universiti Teknologi MARA (UiTM), Research Management Centre (RMC) and Ministry of Higher Education (MOHE) are greatly acknowledged for providing the fund YTR 600-RMC/YTR/5/3 (004/2020) to enable this research to be carried out. The authors would also like to thank the people who were directly or indirectly involved in this research.Copernicus Gesellschaft MbhUniversidade do MinhoSani, Nor HananiTahar, Khairul NizamMaharjan, Gyanu RajaMatos, José C.Muhammad, Muizzuddin20222022-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/1822/89222eng1682-175010.5194/isprs-archives-XLIII-B2-2022-455-2022https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-455-2022info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:08:55Zoai:repositorium.sdum.uminho.pt:1822/89222Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:17:05.301327Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
3D reconstruction of building model using UAV point clouds |
title |
3D reconstruction of building model using UAV point clouds |
spellingShingle |
3D reconstruction of building model using UAV point clouds Sani, Nor Hanani 3D model Point cloud Precision UAV Science & Technology |
title_short |
3D reconstruction of building model using UAV point clouds |
title_full |
3D reconstruction of building model using UAV point clouds |
title_fullStr |
3D reconstruction of building model using UAV point clouds |
title_full_unstemmed |
3D reconstruction of building model using UAV point clouds |
title_sort |
3D reconstruction of building model using UAV point clouds |
author |
Sani, Nor Hanani |
author_facet |
Sani, Nor Hanani Tahar, Khairul Nizam Maharjan, Gyanu Raja Matos, José C. Muhammad, Muizzuddin |
author_role |
author |
author2 |
Tahar, Khairul Nizam Maharjan, Gyanu Raja Matos, José C. Muhammad, Muizzuddin |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Sani, Nor Hanani Tahar, Khairul Nizam Maharjan, Gyanu Raja Matos, José C. Muhammad, Muizzuddin |
dc.subject.por.fl_str_mv |
3D model Point cloud Precision UAV Science & Technology |
topic |
3D model Point cloud Precision UAV Science & Technology |
description |
Photo-realistic 3D model of object cannot be created by using conventional Total Station method. The aim of this study is to generate 3D building model using UAV's dense point clouds. In this research, the ability of remotely detected information for the construction of 3D building models is found to be as specific as UAV datasets, Tacheometry Survey and Traverse Survey. Pix4D and MeshLab software were used in this study to perform image processing of 3D building. The building was built up upon using the information needed from capturing UAV images. This procedure requires the height of building to be measured through conventional method such that of UAV and the height is then compared with a 3D building model. At the end of the process, the comparison of height of building, also known as RMSE, was conducted. The images of building were then processed in Photogrammetry which is the Pix4D software. Using Pix4D, this study proceeded with several processing stages such as camera calibration, photo uploading, building of dense cloud, mesh generation, and model texturing. Those processes were done automatically by using Pix4D tools. High quality of photo-realistic 3D model of building was then successfully constructed. The accuracy assessment was done by comparing the measurement of 3D model of building. Direct measuring of building by using total station had taken place to compare the measurements between 3D model details with actual measurements. The measurement of 3D model of building was done in Pix4D software. The RMSE achieved in this study is 0.015 m which is under reasonable accuracy limit. This study proves that UAV point cloud is capable to produce a very fine 3D model. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z |
dc.type.driver.fl_str_mv |
conference paper |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/89222 |
url |
https://hdl.handle.net/1822/89222 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1682-1750 10.5194/isprs-archives-XLIII-B2-2022-455-2022 https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-455-2022 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Copernicus Gesellschaft Mbh |
publisher.none.fl_str_mv |
Copernicus Gesellschaft Mbh |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
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