Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration

Detalhes bibliográficos
Autor(a) principal: Cunha, Rafael Rodrigues
Data de Publicação: 2022
Outros Autores: Arrabal, Claude Thiago, Dantas, Marcelo Mourão, Bassaneli, Hélio Rodrigues [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.forsciint.2021.111100
http://hdl.handle.net/11449/222952
Resumo: This work evaluated the accuracy of 3D models generated by a DJI Mavic Pro drone with 3DF Zephyr software photogrammetry. The models were compared to models generated by a Trimble X7 laser scanner. The tests were performed in the outdoor area of a vehicle parking inbound to simulate the characteristics of a crime scene. Ground control points (GCPs) were distributed in ten positions within the surroundings. In manual flight, the drone performed nadiral photographs from one side to the other side and with an elliptical 45° center pointed. Three altitudes where tested: 10 m, 20 m and 40 m. The Trimble X7 laser scanner performed six scans and generated one set of point clouds. Drone photogrammetry returned eligible data for distances of 20 m and 40 m with errors of ~0.25 mm. To increase the overlay in the photogrammetry procedure, all photographs from distances of 10–40 m were processed, returning an error of ~0.53 mm. The results of the measured distances, which were manually picked from the GCPs, from the 3D-scanned model and photogrammetric 3D models were then statistically analyzed. The Trimble X7 laser scanner showed an average error of 3 cm, which was approximately equivalent to the results obtained with all images or when using a known scale value for the drone photographs, presenting no significant differences among the evaluated methods.
id UNSP_01f6d6189dfb8f7e5e8c78188d371e7b
oai_identifier_str oai:repositorio.unesp.br:11449/222952
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registrationCrime sceneDroneLaser scanningPhotogrammetryPoint cloudUAVThis work evaluated the accuracy of 3D models generated by a DJI Mavic Pro drone with 3DF Zephyr software photogrammetry. The models were compared to models generated by a Trimble X7 laser scanner. The tests were performed in the outdoor area of a vehicle parking inbound to simulate the characteristics of a crime scene. Ground control points (GCPs) were distributed in ten positions within the surroundings. In manual flight, the drone performed nadiral photographs from one side to the other side and with an elliptical 45° center pointed. Three altitudes where tested: 10 m, 20 m and 40 m. The Trimble X7 laser scanner performed six scans and generated one set of point clouds. Drone photogrammetry returned eligible data for distances of 20 m and 40 m with errors of ~0.25 mm. To increase the overlay in the photogrammetry procedure, all photographs from distances of 10–40 m were processed, returning an error of ~0.53 mm. The results of the measured distances, which were manually picked from the GCPs, from the 3D-scanned model and photogrammetric 3D models were then statistically analyzed. The Trimble X7 laser scanner showed an average error of 3 cm, which was approximately equivalent to the results obtained with all images or when using a known scale value for the drone photographs, presenting no significant differences among the evaluated methods.Superintendência da Polícia Técnico Científica do Estado de São Paulo SPTCUniversidade Estadual Paulista UNESP – Centro Nacional de Monitoramento de Desastres Naturais - CEMADENUniversidade Estadual Paulista UNESP – Centro Nacional de Monitoramento de Desastres Naturais - CEMADENSuperintendência da Polícia Técnico Científica do Estado de São Paulo SPTCUniversidade Estadual Paulista (UNESP)Cunha, Rafael RodriguesArrabal, Claude ThiagoDantas, Marcelo MourãoBassaneli, Hélio Rodrigues [UNESP]2022-04-28T19:47:45Z2022-04-28T19:47:45Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.forsciint.2021.111100Forensic Science International, v. 330.1872-62830379-0738http://hdl.handle.net/11449/22295210.1016/j.forsciint.2021.1111002-s2.0-85120315395Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengForensic Science Internationalinfo:eu-repo/semantics/openAccess2022-04-28T19:47:45Zoai:repositorio.unesp.br:11449/222952Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T19:47:45Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration
title Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration
spellingShingle Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration
Cunha, Rafael Rodrigues
Crime scene
Drone
Laser scanning
Photogrammetry
Point cloud
UAV
title_short Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration
title_full Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration
title_fullStr Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration
title_full_unstemmed Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration
title_sort Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration
author Cunha, Rafael Rodrigues
author_facet Cunha, Rafael Rodrigues
Arrabal, Claude Thiago
Dantas, Marcelo Mourão
Bassaneli, Hélio Rodrigues [UNESP]
author_role author
author2 Arrabal, Claude Thiago
Dantas, Marcelo Mourão
Bassaneli, Hélio Rodrigues [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Superintendência da Polícia Técnico Científica do Estado de São Paulo SPTC
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Cunha, Rafael Rodrigues
Arrabal, Claude Thiago
Dantas, Marcelo Mourão
Bassaneli, Hélio Rodrigues [UNESP]
dc.subject.por.fl_str_mv Crime scene
Drone
Laser scanning
Photogrammetry
Point cloud
UAV
topic Crime scene
Drone
Laser scanning
Photogrammetry
Point cloud
UAV
description This work evaluated the accuracy of 3D models generated by a DJI Mavic Pro drone with 3DF Zephyr software photogrammetry. The models were compared to models generated by a Trimble X7 laser scanner. The tests were performed in the outdoor area of a vehicle parking inbound to simulate the characteristics of a crime scene. Ground control points (GCPs) were distributed in ten positions within the surroundings. In manual flight, the drone performed nadiral photographs from one side to the other side and with an elliptical 45° center pointed. Three altitudes where tested: 10 m, 20 m and 40 m. The Trimble X7 laser scanner performed six scans and generated one set of point clouds. Drone photogrammetry returned eligible data for distances of 20 m and 40 m with errors of ~0.25 mm. To increase the overlay in the photogrammetry procedure, all photographs from distances of 10–40 m were processed, returning an error of ~0.53 mm. The results of the measured distances, which were manually picked from the GCPs, from the 3D-scanned model and photogrammetric 3D models were then statistically analyzed. The Trimble X7 laser scanner showed an average error of 3 cm, which was approximately equivalent to the results obtained with all images or when using a known scale value for the drone photographs, presenting no significant differences among the evaluated methods.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-28T19:47:45Z
2022-04-28T19:47:45Z
2022-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.forsciint.2021.111100
Forensic Science International, v. 330.
1872-6283
0379-0738
http://hdl.handle.net/11449/222952
10.1016/j.forsciint.2021.111100
2-s2.0-85120315395
url http://dx.doi.org/10.1016/j.forsciint.2021.111100
http://hdl.handle.net/11449/222952
identifier_str_mv Forensic Science International, v. 330.
1872-6283
0379-0738
10.1016/j.forsciint.2021.111100
2-s2.0-85120315395
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Forensic Science International
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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_ 1803046034834718720