Publicação
Digital Multispectral Map Reconstruction Using Aerial Imagery
| Resumo: | Advances made in the computer vision field allowed for the establishment of faster and more accurate photogrammetry techniques. Structure from Motion(SfM) is a photogrammetric technique focused on the digital spatial reconstruction of objects based on a sequence of images. The benefit of Unmanned Aerial Vehicle (UAV) platforms allowed the ability to acquire high fidelity imagery intended for environmental mapping. This way, UAV platforms became a heavily adopted method of survey. The combination of SfM and the recent improvements of Unmanned Aerial Vehicle (UAV) platforms granted greater flexibility and applicability, opening a new path for a new remote sensing technique aimed to replace more traditional and laborious approaches often associated with high monetary costs. The continued development of digital reconstruction software and advances in the field of computer processing allowed for a more affordable and higher resolution solution when compared to the traditional methods. The present work proposed a digital reconstruction algorithm based on images taken by a UAV platform inspired by the work made available by the open-source project OpenDroneMap. The aerial images are inserted in the computer vision program and several operations are applied to them, including detection and matching of features, point cloud reconstruction, meshing, and texturing, which results in a final product that represents the surveyed site. Additionally, from the study, it was concluded that an implementation which addresses the processing of thermal images was not integrated in the works of OpenDroneMap. By this point, their work was altered to allow for the reconstruction of thermal maps without sacrificing the resolution of the final model. Standard methods to process thermal images required a larger image footprint (or area of ground capture in a frame), the reason for this is that these types of images lack the presence of invariable features and by increasing the image’s footprint, the number of features present in each frame also rises. However, this method of image capture results in a lower resolution of the final product. The algorithm was developed using open-source libraries. In order to validate the obtained results, this model was compared to data obtained from commercial products, like Pix4D. Furthermore, due to circumstances brought about by the current pandemic, it was not possible to conduct a field study for the comparison and assessment of our results, as such the validation of the models was performed by verifying if the geographic location of the model was performed correctly and by visually assessing the generated maps. |
|---|---|
| Autores principais: | Vong, André Agostinho Cheang do Rosário |
| Assunto: | Remote Sensing Photogrammetry Computer Vision UAV Structure from Motion Digital Reconstruction |
| Ano: | 2021 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| _version_ | 1868982991313698816 |
|---|---|
| author | Vong, André Agostinho Cheang do Rosário |
| author_facet | Vong, André Agostinho Cheang do Rosário |
| author_role | author |
| contributor_name_str_mv | Mora, André Carvalho, João RUN |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Vong, André Agostinho Cheang do Rosário\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Mora, André Carvalho, João RUN |
| datacite.creators.creator.creatorName.fl_str_mv | Vong, André Agostinho Cheang do Rosário |
| datacite.date.Accepted.fl_str_mv | 2021-12-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2022-02-21T14:53:03Z |
| datacite.date.embargoed.fl_str_mv | 2022-02-21T14:53:03Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Remote Sensing Photogrammetry Computer Vision UAV Structure from Motion Digital Reconstruction |
| datacite.titles.title.fl_str_mv | Digital Multispectral Map Reconstruction Using Aerial Imagery |
| dc.contributor.none.fl_str_mv | Mora, André Carvalho, João RUN |
| dc.creator.none.fl_str_mv | Vong, André Agostinho Cheang do Rosário |
| dc.date.Accepted.fl_str_mv | 2021-12-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2022-02-21T14:53:03Z |
| dc.date.embargoed.fl_str_mv | 2022-02-21T14:53:03Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10362/133295 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Remote Sensing Photogrammetry Computer Vision UAV Structure from Motion Digital Reconstruction |
| dc.title.fl_str_mv | Digital Multispectral Map Reconstruction Using Aerial Imagery |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | Advances made in the computer vision field allowed for the establishment of faster and more accurate photogrammetry techniques. Structure from Motion(SfM) is a photogrammetric technique focused on the digital spatial reconstruction of objects based on a sequence of images. The benefit of Unmanned Aerial Vehicle (UAV) platforms allowed the ability to acquire high fidelity imagery intended for environmental mapping. This way, UAV platforms became a heavily adopted method of survey. The combination of SfM and the recent improvements of Unmanned Aerial Vehicle (UAV) platforms granted greater flexibility and applicability, opening a new path for a new remote sensing technique aimed to replace more traditional and laborious approaches often associated with high monetary costs. The continued development of digital reconstruction software and advances in the field of computer processing allowed for a more affordable and higher resolution solution when compared to the traditional methods. The present work proposed a digital reconstruction algorithm based on images taken by a UAV platform inspired by the work made available by the open-source project OpenDroneMap. The aerial images are inserted in the computer vision program and several operations are applied to them, including detection and matching of features, point cloud reconstruction, meshing, and texturing, which results in a final product that represents the surveyed site. Additionally, from the study, it was concluded that an implementation which addresses the processing of thermal images was not integrated in the works of OpenDroneMap. By this point, their work was altered to allow for the reconstruction of thermal maps without sacrificing the resolution of the final model. Standard methods to process thermal images required a larger image footprint (or area of ground capture in a frame), the reason for this is that these types of images lack the presence of invariable features and by increasing the image’s footprint, the number of features present in each frame also rises. However, this method of image capture results in a lower resolution of the final product. The algorithm was developed using open-source libraries. In order to validate the obtained results, this model was compared to data obtained from commercial products, like Pix4D. Furthermore, due to circumstances brought about by the current pandemic, it was not possible to conduct a field study for the comparison and assessment of our results, as such the validation of the models was performed by verifying if the geographic location of the model was performed correctly and by visually assessing the generated maps. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://run.unl.pt/bitstreams/790e1172-2d62-47ad-aeb5-c0e501644f10/download |
| funder_facet_str_mv | FCT{{{_:::_}}}Fundação para a Ciência e a Tecnologia FCT{{{_:::_}}}Fundação para a Ciência e a Tecnologia |
| funding.funder.alternateName_str_mv | FCT FCT |
| funding.funder.identifier_str_mv | http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 |
| funding.funder.name_str_mv | Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia |
| funding.name_str_mv | 6817 - DCRRNI ID 6817 - DCRRNI ID |
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| identifier.url.fl_str_mv | http://hdl.handle.net/10362/133295 |
| inst_facet_str | urn:organizationAcronym:unl{{{_:::_}}}Universidade Nova de Lisboa |
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| institution | Universidade Nova de Lisboa |
| instname_str | Universidade Nova de Lisboa |
| language | eng |
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| network_name_str | Repositório Institucional da UNL |
| oai_identifier_str | oai:run.unl.pt:10362/133295 |
| organization_str_mv | urn:organizationAcronym:unl |
| person_str_mv | Vong, André Agostinho Cheang do Rosário |
| publishDate | 2021 |
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| spelling | engpt_PTAdvances made in the computer vision field allowed for the establishment of faster and more accurate photogrammetry techniques. Structure from Motion(SfM) is a photogrammetric technique focused on the digital spatial reconstruction of objects based on a sequence of images. The benefit of Unmanned Aerial Vehicle (UAV) platforms allowed the ability to acquire high fidelity imagery intended for environmental mapping. This way, UAV platforms became a heavily adopted method of survey. The combination of SfM and the recent improvements of Unmanned Aerial Vehicle (UAV) platforms granted greater flexibility and applicability, opening a new path for a new remote sensing technique aimed to replace more traditional and laborious approaches often associated with high monetary costs. The continued development of digital reconstruction software and advances in the field of computer processing allowed for a more affordable and higher resolution solution when compared to the traditional methods. The present work proposed a digital reconstruction algorithm based on images taken by a UAV platform inspired by the work made available by the open-source project OpenDroneMap. The aerial images are inserted in the computer vision program and several operations are applied to them, including detection and matching of features, point cloud reconstruction, meshing, and texturing, which results in a final product that represents the surveyed site. Additionally, from the study, it was concluded that an implementation which addresses the processing of thermal images was not integrated in the works of OpenDroneMap. By this point, their work was altered to allow for the reconstruction of thermal maps without sacrificing the resolution of the final model. Standard methods to process thermal images required a larger image footprint (or area of ground capture in a frame), the reason for this is that these types of images lack the presence of invariable features and by increasing the image’s footprint, the number of features present in each frame also rises. However, this method of image capture results in a lower resolution of the final product. The algorithm was developed using open-source libraries. In order to validate the obtained results, this model was compared to data obtained from commercial products, like Pix4D. Furthermore, due to circumstances brought about by the current pandemic, it was not possible to conduct a field study for the comparison and assessment of our results, as such the validation of the models was performed by verifying if the geographic location of the model was performed correctly and by visually assessing the generated maps.application/pdfpt_PTDigital Multispectral Map Reconstruction Using Aerial ImageryVong, André Agostinho Cheang do RosárioMora, AndréCarvalho, JoãoHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.pt2022-02-21T14:53:03Z2021-122021-12-01T00:00:00ZHandlehttp://hdl.handle.net/10362/133295http://purl.org/coar/access_right/c_abf2open accessRemote SensingPhotogrammetryComputer VisionUAVStructure from MotionDigital Reconstruction13958813 bytesFundação para a Ciência e a TecnologiaCOPELABS - Cognitive and People-centric Computing R&D Unit6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaCentre of Technology and Systems6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/790e1172-2d62-47ad-aeb5-c0e501644f10/download |
| spellingShingle | Digital Multispectral Map Reconstruction Using Aerial Imagery Vong, André Agostinho Cheang do Rosário Remote Sensing Photogrammetry Computer Vision UAV Structure from Motion Digital Reconstruction |
| status | SINGLETON |
| subject.fl_str_mv | Remote Sensing Photogrammetry Computer Vision UAV Structure from Motion Digital Reconstruction |
| title | Digital Multispectral Map Reconstruction Using Aerial Imagery |
| title_full | Digital Multispectral Map Reconstruction Using Aerial Imagery |
| title_fullStr | Digital Multispectral Map Reconstruction Using Aerial Imagery |
| title_full_unstemmed | Digital Multispectral Map Reconstruction Using Aerial Imagery |
| title_short | Digital Multispectral Map Reconstruction Using Aerial Imagery |
| title_sort | Digital Multispectral Map Reconstruction Using Aerial Imagery |
| topic | Remote Sensing Photogrammetry Computer Vision UAV Structure from Motion Digital Reconstruction |
| topic_facet | Remote Sensing Photogrammetry Computer Vision UAV Structure from Motion Digital Reconstruction |
| url | http://hdl.handle.net/10362/133295 |
| visible | 1 |