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Point clouds for direct pedestrian pathfinding in urban environments / Jesus Balado in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 148 (February 2019) . - pp 184 - 196 Titre : Point clouds for direct pedestrian pathfinding in urban environments Type de document : Article/Communication Auteurs : Jesus Balado, Auteur ; Lucia Diaz-Vilarino, Auteur ; Pedro Arias, Auteur ; Henrique Lorenzo, Auteur Année de publication : 2019 Article en page(s) : pp 184 - 196 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accessibilité [Termes IGN] chemin le plus court, algorithme du [Termes IGN] détection de partie cachée [Termes IGN] données localisées 3D [Termes IGN] graphe [Termes IGN] itinéraire piétionnier [Termes IGN] milieu urbain [Termes IGN] navigation pédestre [Termes IGN] objet mobile [Termes IGN] objet statique [Termes IGN] semis de points Mots-clés libres : espace urbain navigable pour piéton Résumé : (Auteur) Pathfinding applications for the citizen in urban environments are usually designed from the perspective of a driver, not being effective for pedestrians. In addition, urban scenes have multiple elements that interfere with pedestrian routes and navigable space. In this paper, a methodology for the direct use of point clouds for pathfinding in urban environments is presented, solving the main limitations for this purpose: (a) the excessive number of points is reduced for transformation into nodes on the final graph, (b) urban static elements acting as permanent obstacles, such as furniture and trees, are delimited and differentiated from dynamic elements such as pedestrians, (c) occlusions on ground elements are corrected to enable a complete graph modelling, and (d) navigable space is delimited from free unobstructed space according to two motor skills (pedestrians without reduced mobility and wheelchairs). The methodology is tested into three different streets sampled as point clouds by mobile laser scanning (MLS) systems: an intersection of several streets with ground composed of sidewalks at different heights; an avenue with wide sidewalks, trees and cars parked on one side; and a street with a single-lane road and narrow sidewalks. By applying Dijkstra pathfinding algorithm to the resulting graphs, the correct viability of the generated routes has been verified based on a visual analysis of the generated routes on the point cloud and on the knowledge of the urban study area. The methodology enables the automatic generation of graphs representing the navigable urban space, on which safe and real routes for different motor skills can be calculated. Numéro de notice : A2019-074 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.004 Date de publication en ligne : 15/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.004 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92161 [article]

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