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Three-dimensional building façade segmentation and opening area detection from point clouds / S.M. Iman Zolanvari in ISPRS Journal of photogrammetry and remote sensing, vol 143 (September 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 143 (September 2018) . - pp 134 - 149 Titre : Three-dimensional building façade segmentation and opening area detection from point clouds Type de document : Article/Communication Auteurs : S.M. Iman Zolanvari, Auteur ; Debra F. Laefer, Auteur ; Atteyeh S. Natanzi, Auteur Année de publication : 2018 Article en page(s) : pp 134 - 149 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction de traits caractéristiques [Termes IGN] reconstruction 3D du bâti [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] toit Résumé : (Auteur) Laser scanning generates a point cloud from which geometries can be extracted, but most methods struggle to do this automatically, especially for the entirety of an architecturally complex building (as opposed to that of a single façade). To address this issue, this paper introduces the Improved Slicing Method (ISM), an innovative and computationally-efficient method for three-dimensional building segmentation. The method is also able to detect opening boundaries even on roofs (e.g. chimneys), as well as a building’s overall outer boundaries using a local density analysis technique. The proposed procedure is validated by its application to two architecturally complex, historic brick buildings. Accuracies of at least 86% were achieved, with computational times as little as 0.53 s for detecting features from a data set of 5.0 million points. The accuracy more than rivalled the current state of the art, while being up to six times faster and with the further advantage of requiring no manual intervention or reliance on a priori information. Numéro de notice : A2018-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.004 Date de publication en ligne : 09/05/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90592 [article]

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