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Automatic roof model reconstruction from ALS data and 2D ground plans based on side projection and the TMR [TIN-Merging and Reshaping] algorithm / J. Rau in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 6 supplement (December 2011)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 66 n° 6 supplement (December 2011) . - pp 13 - 27 Titre : Automatic roof model reconstruction from ALS data and 2D ground plans based on side projection and the TMR [TIN-Merging and Reshaping] algorithm Type de document : Article/Communication Auteurs : J. Rau, Auteur ; B. Lin, Auteur Année de publication : 2011 Article en page(s) : pp 13 - 27 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] fusion de données [Termes IGN] lasergrammétrie [Termes IGN] modélisation 3D [Termes IGN] reconstruction 3D du bâti [Termes IGN] semis de points [Termes IGN] télémétrie laser aéroporté [Termes IGN] toit [Termes IGN] Triangulated Irregular Network Résumé : (Auteur) This paper presents an automatic roof model reconstruction method based on the side projection of airborne laser scanning (ALS) data. The proposed approach first detects the building’s primary orientation and decomposes multi-layer roofs into a single one. Then, 3D structural lines are detected and restored from the projected point clouds. Finally, a line-based roof model reconstruction algorithm, namely TIN-Merging and Reshaping (TMR), is proposed. The originality for 3D roof modeling is to perform geometric analysis and topology reconstruction from two 2D projections and then reshapes the roof using elevation information from the 3D structural lines or ALS data. Experimental results indicate a nearly 100% success rate for topology reconstruction can be achieved provided that the 3D structural lines can be enclosed as polygons. However, the success rate of the Reshaping stage is dependent on the complexity of the rooftop structure. With the exception of domed and multiple orientations roofs, which are not considered in the developed method, we achieve success rates around 92–95%. As for absolute accuracy, less that 50 cm of root-mean-square error is observed in all X–Y–Z directions. The results demonstrate that the proposed scheme is robust and accurate even when a group of connected buildings with multiple layers and mixed roof types is processed. Numéro de notice : A2011-515 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2011.09.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2011.09.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31409 [article]

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