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Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding / Florian W. Fichtner in Transactions in GIS, vol 22 n° 1 (February 2018)  

Public [article]  inTransactions in GIS > vol 22 n° 1 (February 2018) . - pp 233 - 248 Titre : Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding Type de document : Article/Communication Auteurs : Florian W. Fichtner, Auteur ; Abdoulaye A. Diakité, Auteur ; Sisi Zlatanova, Auteur ; Robert Voûte, Auteur Année de publication : 2018 Article en page(s) : pp 233 - 248 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] calcul d'itinéraire [Termes IGN] espace intérieur vide [Termes IGN] information sémantique [Termes IGN] octree [Termes IGN] positionnement en intérieur [Termes IGN] semis de points Résumé : (auteur) 3D indoor navigation in multi‐story buildings and under changing environments is still difficult to perform. 3D models of buildings are commonly not available or outdated. 3D point clouds turned out to be a very practical way to capture 3D interior spaces and provide a notion of an empty space. Therefore, pathfinding in point clouds is rapidly emerging. However, processing of raw point clouds can be very expensive, as these are semantically poor and unstructured data. In this article we present an innovative octree‐based approach for processing of 3D indoor point clouds for the purpose of multi‐story pathfinding. We semantically identify the construction elements, which are of importance for the indoor navigation of humans (i.e., floors, walls, stairs, and obstacles), and use these to delineate the available navigable space. To illustrate the usability of this approach, we applied it to real‐world data sets and computed paths considering user constraints. The structuring of the point cloud into an octree approximation improves the point cloud processing and provides a structure for the empty space of the point cloud. It is also helpful to compute paths sufficiently accurate in their consideration of the spatial complexity. The entire process is automatic and able to deal with a large number of multi‐story indoor environments. Numéro de notice : A2018-067 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12308 En ligne : https://doi.org/10.1111/tgis.12308 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89423 [article]

Project pointless : pathfinding through identified empty space in point clouds / Tom Broersen in GIM international, vol 30 n° 4 (April 2016)

Public [article]  inGIM international > vol 30 n° 4 (April 2016) . - pp 21 - 23 Titre : Project pointless : pathfinding through identified empty space in point clouds Type de document : Article/Communication Auteurs : Tom Broersen, Auteur ; Florian W. Fichtner, Auteur ; Ivo de Liefde, Auteur Année de publication : 2016 Article en page(s) : pp 21 - 23 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] espace intérieur vide [Termes IGN] octree [Termes IGN] semis de points Résumé : (éditeur) Indoor point clouds are useful for many applications, such as for pathfinding through empty, collision-free space. Fast-performing methods are required to identify this empty space because the indoor environment changes frequently and often does not follow the architectural design. As part of the Synthesis Project 2015, students of the MSc in Geomatics programme at Delft University of Technology have developed a method to efficiently identify and structure connected empty space in point clouds. Numéro de notice : A2016-214 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80681 [article]