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An indoor navigation model and its network extraction / Filippo Mortari in Applied geomatics, Vol 11 n° 4 (December 2019)  

Public [article]  inApplied geomatics > Vol 11 n° 4 (December 2019) . - pp 413–427 Titre : An indoor navigation model and its network extraction Type de document : Article/Communication Auteurs : Filippo Mortari, Auteur ; Eliseo Clementini, Auteur ; Sisi Zlatanova, Auteur ; Liu Liu, Auteur Année de publication : 2019 Article en page(s) : pp 413–427 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] axe médian [Termes IGN] CityGML [Termes IGN] diagramme de Voronoï [Termes IGN] espace topologique [Termes IGN] extraction automatique [Termes IGN] extraction de données [Termes IGN] modèle géométrique du bâti [Termes IGN] modèle numérique du bâti [Termes IGN] modélisation 3D [Termes IGN] positionnement en intérieur [Termes IGN] raisonnement spatiotemporel [Termes IGN] représentation spatio-sémantique Résumé : (auteur) We propose a navigation model for indoor environments that combines a 3D geometric modeling of buildings with connection properties of spaces and semantic elements such as openings and installations. The model is an extension of the IndoorGML standard navigation module with a twofold benefit: the extension facilitated the data import from the international standard CityGML and introduced the semantics of various fixtures in indoor space of buildings making the navigation model more suitable for human needs. Several experiments have been conducted by extracting networks from CityGML data and performing a comparison with other network construction techniques. The second contribution of the paper is an algorithm for the automatic extraction of the navigation network. Such an algorithm is a hybrid solution between medial axis approaches and visibility graph approaches. Normally, medial axes approaches are a good representation of human navigation in narrow corridors, especially to avoid obstacles, but introduce distortions in open space. On the other hand, visibility approaches work better in open spaces. In our extraction technique, the resulting network takes advantages of both approaches and better mimics human beings’ navigation in indoor environments. Numéro de notice : A2019-534 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-019-00273-8 Date de publication en ligne : 17/06/2019 En ligne : https://doi.org/10.1007/s12518-019-00273-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94129 [article]