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Pedestrian network extraction from fused aerial imagery (orthoimages) and laser imagery (lidar) / Piyawan Kasemsuppakorn in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 4 (April 2013)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 4 (April 2013) . - pp 369 - 379 Titre : Pedestrian network extraction from fused aerial imagery (orthoimages) and laser imagery (lidar) Type de document : Article/Communication Auteurs : Piyawan Kasemsuppakorn, Auteur ; Hassan A. Karimi, Auteur Année de publication : 2013 Article en page(s) : pp 369 - 379 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] extraction automatique [Termes IGN] fusion de données [Termes IGN] image aérienne [Termes IGN] itinéraire piétionnier [Termes IGN] orthoimage [Termes IGN] piéton [Termes IGN] vectorisation Résumé : (Auteur) A pedestrian network is a topological map that contains the geometric relationship between pedestrian path segments (e.g., sidewalk, crosswalk, footpath), which is needed in a variety of applications, such as pedestrian navigation services. However, current pedestrian networks are not widely available. In an effort to provide an automatic means for creating pedestrian networks, this paper presents a methodology for extracting pedestrian network from aerial and laser images. The methodology consists of data preparation and four steps: object filtering, pedestrian path region extraction, pedestrian network construction, and raster to vector conversion. An experiment, using ten images, was conducted to evaluate the performance of the methodology. Evaluation results indicate that the methodology can extract sidewalk, crosswalk, footpath, and building entrances; it collects pedestrian networks with 61 percent geometrical completeness, 67.35 percent geometrical correctness, 71 percent topological completeness and 51.38 percent topological correctness. Numéro de notice : A2013-206 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.4.369 En ligne : https://doi.org/10.14358/PERS.79.4.369 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32344 [article]