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Segmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 48 n° 3 Tome 2 (March 2010) . - pp 1554 - 1567 Titre : Segmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds Type de document : Article/Communication Auteurs : A. Sampath, Auteur ; J. Shan, Auteur Année de publication : 2010 Article en page(s) : pp 1554 - 1567 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse de groupement [Termes IGN] cohérence géométrique [Termes IGN] détection du bâti [Termes IGN] diagramme de Voronoï [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] intégrité topologique [Termes IGN] reconstruction 3D du bâti [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] similitude [Termes IGN] toit Résumé : (Auteur) This paper presents a solution framework for the segmentation and reconstruction of polyhedral building roofs from aerial LIght Detection And Ranging (lidar) point clouds. The eigenanalysis is first carried out for each roof point of a building within its Voronoi neighborhood. Such analysis not only yields the surface normal for each lidar point but also separates the lidar points into planar and nonplanar ones. In the second step, the surface normals of all planar points are clustered with the fuzzy k-means method. To optimize this clustering process, a potential-based approach is used to estimate the number of clusters, while considering both geometry and topology for the cluster similarity. The final step of segmentation separates the parallel and coplanar segments based on their distances and connectivity, respectively. Building reconstruction starts with forming an adjacency matrix that represents the connectivity of the segmented planar segments. A roof interior vertex is determined by intersecting all planar segments that meet at one point, whereas constraints in the form of vertical walls or boundary are applied to determine the vertices on the building outline. Finally, an extended boundary regularization approach is developed based on multiple parallel and perpendicular line pairs to achieve topologically consistent and geometrically correct building models. This paper describes the detail principles and implementation steps for the aforementioned solution framework. Results of a number of buildings with diverse roof complexities are presented and evaluated. Numéro de notice : A2010-272 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2009.2030180 Date de publication en ligne : 03/11/2009 En ligne : https://doi.org/10.1109/TGRS.2009.2030180 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30466 [article]

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Building boundary tracing and regularization from airborne lidar point clouds / A. Sampath in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 7 (July 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 7 (July 2007) . - pp 805 - 812 Titre : Building boundary tracing and regularization from airborne lidar point clouds Type de document : Article/Communication Auteurs : A. Sampath, Auteur ; J. Shan, Auteur Année de publication : 2007 Article en page(s) : pp 805 - 812 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] correction géométrique [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] lasergrammétrie [Termes IGN] lissage de données [Termes IGN] Maryland (Etats-Unis) [Termes IGN] reconstruction 3D du bâti [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] Toronto Résumé : (Auteur) Building boundary is necessary for the real estate industry, flood management, and homeland security applications. The extraction of building boundary is also a crucial and difficult step towards generating city models. This study presents an approach to the tracing and regularization of building boundary from raw lidar point clouds. The process consists of a sequence of four steps: separate building and non-building lidar points; segment lidar points that belong to the same building; trace building boundary points; and regularize the boundary. For separation, a slope based 1D bi-directional filter is used. The segmentation step is a region-growing approach. By modifying a convex hull formation algorithm, the building boundary points are traced and connected to form an approximate boundary. In the final step, all boundary points are included in a hierarchical least squares solution with perpendicularity constraints to determine a regularized rectilinear boundary. Our tests conclude that the uncertainty of regularized building boundary tends to be linearly proportional to the lidar point spacing. It is shown that the regularization precision is at 18 percent to 21 percent of the lidar point spacing, and the maximum offset of the determined building boundary from the original lidar points is about the same as the lidar point spacing. Limitation of lidar data resolution and errors in previous filtering processes may cause artefacts in the final regularized building boundary. This paper presents the mathematical and algorithmic formulations along with stepwise illustrations. Results from Baltimore city, Toronto city, and Purdue University campus are evaluated. Copyright ASPRS Numéro de notice : A2007-314 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.7.805 En ligne : http://dx.doi.org/10.14358/PERS.73.7.805 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28677 [article]