Context-based urban terrain reconstruction from uav-videos for geoinformation applications

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dc.identifier.uri http://dx.doi.org/10.15488/1102
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/1126
dc.contributor.author Bulatov, D.
dc.contributor.author Solbrig, P.
dc.contributor.author Gross H.
dc.contributor.author Wernerus, P.
dc.contributor.author Repasi, E.
dc.contributor.author Heipke, Christian
dc.date.accessioned 2017-02-03T08:18:40Z
dc.date.available 2017-02-03T08:18:40Z
dc.date.issued 2011
dc.identifier.citation Bulatov, D.; Solbrig, P.; Gross, H.; Wernerus, P.; Repasi, E. et al.: Context-based urban terrain reconstruction from uav-videos for geoinformation applications. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: [International Conference On Unmanned Aerial Vehicle In Geomatics (UAV-G)] 38-1 (2011), Nr. C22, S. 75-80. DOI: https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-75-2011
dc.description.abstract Urban terrain reconstruction has many applications in areas of civil engineering, urban planning, surveillance and defense research. Therefore the needs of covering ad-hoc demand and performing a close-range urban terrain reconstruction with miniaturized and relatively inexpensive sensor platforms are constantly growing. Using (miniaturized) unmanned aerial vehicles, (M) UAVs, represents one of the most attractive alternatives to conventional large-scale aerial imagery. We cover in this paper a four-step procedure of obtaining georeferenced 3D urban models from video sequences. The four steps of the procedure - orientation, dense reconstruction, urban terrain modeling and geo-referencing - are robust, straight-forward, and nearly fully-automatic. The two last steps - namely, urban terrain modeling from almost-nadir videos and co-registration of models - represent the main contribution of this work and will therefore be covered with more detail. The essential substeps of the third step include digital terrain model (DTM) extraction, segregation of buildings from vegetation, as well as instantiation of building and tree models. The last step is subdivided into quasi-intrasensorial registration of Euclidean reconstructions and intersensorial registration with a geo-referenced orthophoto. Finally, we present reconstruction results from a real data-set and outline ideas for future work. eng
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartof International Conference on Unmanned Aerial Vehicle in Geomatics (UAV-g), September 14-16, 2011, Zurich, Switzerland
dc.relation.ispartofseries International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: [International Conference On Unmanned Aerial Vehicle In Geomatics (UAV-G)] 38-1 (2011), Nr. C22
dc.rights CC BY 3.0
dc.rights.uri https://creativecommons.org/licenses/by/3.0/
dc.subject UAVs eng
dc.subject Photogrammetry eng
dc.subject Sensor Orientation eng
dc.subject Urban Terrain Reconstruction eng
dc.subject images eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.title Context-based urban terrain reconstruction from uav-videos for geoinformation applications
dc.type article
dc.type conferenceObject
dc.type Text
dc.relation.issn 2194-9034
dc.relation.doi https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-75-2011
dc.bibliographicCitation.issue C22
dc.bibliographicCitation.volume 38-1
dc.bibliographicCitation.firstPage 75
dc.bibliographicCitation.lastPage 80
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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