A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software

In recent years, the generation of accurate topographic reconstructions has found applications ranging from geomorphic sciences to remote sensing and urban planning, among others. The production of high resolution, high-quality digital elevation models (DEMs) requires a significant investment in per...

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Autores:
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/8910
Acceso en línea:
https://hdl.handle.net/20.500.12585/8910
Palabra clave:
Geomatics
Open source software
Structure from motion
Antennas
Cameras
Cost effectiveness
Object recognition
Open systems
Optical radar
Photogrammetry
Pipelines
Remote sensing
Repair
Rock mechanics
Surveying
Tracking radar
Unmanned aerial vehicles (UAV)
Verification
Co-ordinate system
Computer vision techniques
Digital elevation model
Experimental verification
Geomatics
Ground control points
Structure from motion
Topographic reconstruction
Open source software
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restrictedAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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network_name_str Repositorio Institucional UTB
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dc.title.none.fl_str_mv A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software
title A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software
spellingShingle A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software
Geomatics
Open source software
Structure from motion
Antennas
Cameras
Cost effectiveness
Object recognition
Open systems
Optical radar
Photogrammetry
Pipelines
Remote sensing
Repair
Rock mechanics
Surveying
Tracking radar
Unmanned aerial vehicles (UAV)
Verification
Co-ordinate system
Computer vision techniques
Digital elevation model
Experimental verification
Geomatics
Ground control points
Structure from motion
Topographic reconstruction
Open source software
title_short A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software
title_full A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software
title_fullStr A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software
title_full_unstemmed A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software
title_sort A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source software
dc.contributor.editor.none.fl_str_mv Serrano C. J.E.
Martínez-Santos, Juan Carlos
dc.subject.keywords.none.fl_str_mv Geomatics
Open source software
Structure from motion
Antennas
Cameras
Cost effectiveness
Object recognition
Open systems
Optical radar
Photogrammetry
Pipelines
Remote sensing
Repair
Rock mechanics
Surveying
Tracking radar
Unmanned aerial vehicles (UAV)
Verification
Co-ordinate system
Computer vision techniques
Digital elevation model
Experimental verification
Geomatics
Ground control points
Structure from motion
Topographic reconstruction
Open source software
topic Geomatics
Open source software
Structure from motion
Antennas
Cameras
Cost effectiveness
Object recognition
Open systems
Optical radar
Photogrammetry
Pipelines
Remote sensing
Repair
Rock mechanics
Surveying
Tracking radar
Unmanned aerial vehicles (UAV)
Verification
Co-ordinate system
Computer vision techniques
Digital elevation model
Experimental verification
Geomatics
Ground control points
Structure from motion
Topographic reconstruction
Open source software
description In recent years, the generation of accurate topographic reconstructions has found applications ranging from geomorphic sciences to remote sensing and urban planning, among others. The production of high resolution, high-quality digital elevation models (DEMs) requires a significant investment in personnel time, hardware, and software. Photogrammetry offers clear advantages over other methods of collecting geomatic information. Airborne cameras can cover large areas more quickly than ground survey techniques, and the generated Photogrammetry-based DEMs often have higher resolution than models produced with other remote sensing methods such as LIDAR (Laser Imaging Detection and Ranging) or RADAR (radar detection and ranging). In this work, we introduce a Structure from Motion (SfM) pipeline using Unmanned Aerial Vehicles (UAVs) for generating DEMs for performing topographic reconstructions and assessing the microtopography of a terrain. SfM is a computer vision technique that consists in estimating the 3D coordinates of many points in a scene using two or more 2D images acquired from different positions. By identifying common points in the images both the camera position (motion) and the 3D locations of the points (structure) are obtained. The output from an SfM stage is a sparse point cloud in a local XYZ coordinate system. We edit the obtained point in MeshLab to remove unwanted points, such as those from vehicles, roofs, and vegetation. We scale the XYZ point clouds using Ground Control Points (GCP) and GPS information. This process enables georeferenced metric measurements. For the experimental verification, we reconstructed a terrain suitable for subsequent analysis using GIS software. Encouraging results show that our approach is highly cost-effective, providing a means for generating high-quality, low-cost DEMs. © Springer Nature Switzerland AG 2018.
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2020-03-26T16:32:35Z
dc.date.available.none.fl_str_mv 2020-03-26T16:32:35Z
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dc.type.spa.none.fl_str_mv Conferencia
status_str publishedVersion
dc.identifier.citation.none.fl_str_mv Communications in Computer and Information Science; Vol. 885, pp. 213-225
dc.identifier.isbn.none.fl_str_mv 9783319989976
dc.identifier.issn.none.fl_str_mv 18650929
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/8910
dc.identifier.doi.none.fl_str_mv 10.1007/978-3-319-98998-3_17
dc.identifier.instname.none.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.none.fl_str_mv Repositorio UTB
dc.identifier.orcid.none.fl_str_mv 57204065355
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identifier_str_mv Communications in Computer and Information Science; Vol. 885, pp. 213-225
9783319989976
18650929
10.1007/978-3-319-98998-3_17
Universidad Tecnológica de Bolívar
Repositorio UTB
57204065355
24329839300
56682678200
57200615582
7004348301
36142156300
url https://hdl.handle.net/20.500.12585/8910
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.conferencedate.none.fl_str_mv 26 September 2018 through 28 September 2018
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dc.rights.cc.none.fl_str_mv Atribución-NoComercial 4.0 Internacional
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Atribución-NoComercial 4.0 Internacional
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dc.format.medium.none.fl_str_mv Recurso electrónico
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dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054350508&doi=10.1007%2f978-3-319-98998-3_17&partnerID=40&md5=6fa9e5e6a5410c02c669bb5dc5e2af6f
institution Universidad Tecnológica de Bolívar
dc.source.event.none.fl_str_mv 13th Colombian Conference on Computing, CCC 2018
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spelling Serrano C. J.E.Martínez-Santos, Juan CarlosMeza J.Marrugo A.G.Sierra E.Guerrero M.Meneses J.Romero L.A.2020-03-26T16:32:35Z2020-03-26T16:32:35Z2018Communications in Computer and Information Science; Vol. 885, pp. 213-225978331998997618650929https://hdl.handle.net/20.500.12585/891010.1007/978-3-319-98998-3_17Universidad Tecnológica de BolívarRepositorio UTB57204065355243298393005668267820057200615582700434830136142156300In recent years, the generation of accurate topographic reconstructions has found applications ranging from geomorphic sciences to remote sensing and urban planning, among others. The production of high resolution, high-quality digital elevation models (DEMs) requires a significant investment in personnel time, hardware, and software. Photogrammetry offers clear advantages over other methods of collecting geomatic information. Airborne cameras can cover large areas more quickly than ground survey techniques, and the generated Photogrammetry-based DEMs often have higher resolution than models produced with other remote sensing methods such as LIDAR (Laser Imaging Detection and Ranging) or RADAR (radar detection and ranging). In this work, we introduce a Structure from Motion (SfM) pipeline using Unmanned Aerial Vehicles (UAVs) for generating DEMs for performing topographic reconstructions and assessing the microtopography of a terrain. SfM is a computer vision technique that consists in estimating the 3D coordinates of many points in a scene using two or more 2D images acquired from different positions. By identifying common points in the images both the camera position (motion) and the 3D locations of the points (structure) are obtained. The output from an SfM stage is a sparse point cloud in a local XYZ coordinate system. We edit the obtained point in MeshLab to remove unwanted points, such as those from vehicles, roofs, and vegetation. We scale the XYZ point clouds using Ground Control Points (GCP) and GPS information. This process enables georeferenced metric measurements. For the experimental verification, we reconstructed a terrain suitable for subsequent analysis using GIS software. Encouraging results show that our approach is highly cost-effective, providing a means for generating high-quality, low-cost DEMs. © Springer Nature Switzerland AG 2018.Acknowledgement. This work has been partly funded by Universidad Tecnológica de Bolívar project (FI2006T2001). E. Sierra thanks Universidad Tecnológica de Bolívar for a Masters degree scholarship.Recurso electrónicoapplication/pdfengSpringer Verlaghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85054350508&doi=10.1007%2f978-3-319-98998-3_17&partnerID=40&md5=6fa9e5e6a5410c02c669bb5dc5e2af6f13th Colombian Conference on Computing, CCC 2018A structure-from-motion pipeline for topographic reconstructions using unmanned aerial vehicles and open source softwareinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fGeomaticsOpen source softwareStructure from motionAntennasCamerasCost effectivenessObject recognitionOpen systemsOptical radarPhotogrammetryPipelinesRemote sensingRepairRock mechanicsSurveyingTracking radarUnmanned aerial vehicles (UAV)VerificationCo-ordinate systemComputer vision techniquesDigital elevation modelExperimental verificationGeomaticsGround control pointsStructure from motionTopographic reconstructionOpen source software26 September 2018 through 28 September 2018Nelson, A., Reuter, H., Gessler, P., DEM production methods and sources (2009) Dev. Soil Sci., 33, pp. 65-85Carbonneau, P.E., Dietrich, J.T., Cost-effective non-metric photogrammetry from consumer-grade sUAS: Implications for direct georeferencing of structure from motion photogrammetry (2016) Earth Surf. Process. Land., 42, pp. 473-486Nex, F., Remondino, F., UAV for 3D mapping applications: A review (2014) Appl. Geomat., 6 (1), pp. 1-15James, M., Robson, S., Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application (2012) J. Geophys. Res. Earth Surf., 117 (F3)Fonstad, M.A., Dietrich, J.T., Courville, B.C., Jensen, J.L., Carbonneau, P.E., Topographic structure from motion: A new development in photogrammetric measurement (2013) Earth Surf. Process. Land., 38, pp. 421-430Goesele, M., Curless, B., Seitz, S.M., Multi-view stereo revisited (2006) 2009 IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2009, pp. 2402-2409. , IEEEAgisoft Photoscan Professional, , http://www.agisoft.com/downloads/installer/ https://github.com/mapillary/OpenSfMOpendronemap, , https://github.com/OpenDroneMap/OpenDroneMapBradski, G., Kaehler, A., OpenCV. Dr. Dobb’s (2000) J. Softw. Tools., 3 https://www.altizure.comCignoni, P., Callieri, M., Corsini, M., Dellepiane, M., Ganovelli, F., Ranzuglia, G., MeshLab: An open-source mesh processing tool (2008) Eurographics Italian Chapter Conference, 2008, pp. 129-136Duane, C.B., Close-range camera calibration (1971) Photogram. Eng, 37 (8), pp. 855-866 https://maps.google.comTuytelaars, T., Mikolajczyk, K., Local invariant feature detectors: A survey (2008) Found. Trends® Comput. Graph. Vis., 3 (3), pp. 177-280Bolick, L., Harguess, J., A study of the effects of degraded imagery on tactical 3D model generation using structure-from-motion (2016) Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XIII, 9828. , International Society for Optics and PhotonicsGrauman, K., Leibe, B., Visual object recognition (2011) Synthesis Lectures on Artificial Intelligence and Machine Learning, 5 (2), pp. 1-181Lindeberg, T., Feature detection with automatic scale selection (1998) Int. J. Comput. Vis., 30 (2), pp. 79-116Muja, M., Lowe, D.G., Fast approximate nearest neighbors with automatic algorithm configuration (2009) VISAPP (1), 2 (331-340), p. 2Triggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W., Bundle adjustment—a modern synthesis (2000) IWVA 1999. LNCS, 1883, pp. 298-372. , https://doi.org/10.1007/3-540-44480-721, Triggs, B., Zisserman, A., Szeliski, R. (eds.), Springer, HeidelbergFurukawa, Y., Ponce, J., Accurate, dense, and robust multiview stereopsis (2010) IEEE Trans. Pattern Anal. Mach. Intell., 32 (8), pp. 1362-1376Adorjan, M., (2016) Opensfm Ein Kollaboratives Structure-From-Motion System, , betreuer/in (nen): M. wimmer, m. birsakinstitut für computergraphik und algorithmen. abschlussprüfung: 02.05.2016http://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/8910/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/8910oai:repositorio.utb.edu.co:20.500.12585/89102023-05-26 16:29:46.39Repositorio Institucional UTBrepositorioutb@utb.edu.co