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Auteur A. Nyaruhuma |
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Verification of 2D building outlines using oblique airborne images / A. Nyaruhuma in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
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Titre : Verification of 2D building outlines using oblique airborne images Type de document : Article/Communication Auteurs : A. Nyaruhuma, Auteur ; Markus Gerke, Auteur ; M. George Vosselman, Auteur ; E.G. Mtalo, Auteur Année de publication : 2012 Article en page(s) : pp 62 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] arbre aléatoire
[Termes IGN] base de données foncières
[Termes IGN] bâtiment
[Termes IGN] boosting adapté
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] contour
[Termes IGN] image aérienne oblique
[Termes IGN] logique floueRésumé : (Auteur) Oblique airborne images are interesting not only for visualization but also for the acquisition and updating of geo-spatial vector data. This is because side views of vertical structures, such as buildings, are present in those images. In recent years, techniques for automatic verification of building outlines have been proposed. These techniques utilized color, texture and height from vertical images or range data while oblique images contain façade information that can also be used to identify buildings. This paper presents a methodology to verify 2D building outlines in a cadastral dataset by using oblique airborne images. The method searches for clues such as building edges, wall façade edges and texture. The 2D clues in images taken from different perspectives but expected to contain the same wall are transformed to 3D, combined and used for a verification of the particular wall. Unlike methods that use vertical images or LIDAR, walls are verified individually and then the results are combined for the building. We compare three methods for combining wall-based evidence. Experiments using almost 700 buildings show that best results are obtained using Adaptive Boosting where – with a bias for better identification of demolished buildings – 100% of demolished buildings are identified and 91% of existing buildings are confirmed. The other two methods are Random Trees and a variant of the Dempster–Shafer approach combined with fuzzy reasoning and they only show some minor differences to the Adaptive Boosting result. The research as presented in this paper demonstrates the potential of oblique images, but some further work has to be done, including the identification of modified buildings and the extension towards verification of 3D building models. Numéro de notice : A2012-348 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.04.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31794
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