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

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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

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/1102

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Sum total of downloads: 313




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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.
License of this version: CC BY 3.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2011
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 153 48.88%
2 image of flag of United States United States 45 14.38%
3 image of flag of China China 13 4.15%
4 image of flag of Korea, Republic of Korea, Republic of 8 2.56%
5 image of flag of India India 8 2.56%
6 image of flag of United Kingdom United Kingdom 8 2.56%
7 image of flag of Australia Australia 7 2.24%
8 image of flag of Japan Japan 6 1.92%
9 image of flag of No geo information available No geo information available 5 1.60%
10 image of flag of Russian Federation Russian Federation 5 1.60%
    other countries 55 17.57%

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