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GEOBIA 2016, 6th international conference on geographic object-based image analysis : Solutions and synergies 14/09/2016 16/09/2016 Enschede Pays-Bas Open Access Proceedings
nom du congrès :
GEOBIA 2016, 6th international conference on geographic object-based image analysis : Solutions and synergies
début du congrès :
14/09/2016
fin du congrès :
16/09/2016
ville du congrès :
Enschede
pays du congrès :
Pays-Bas
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Affiner la recherche Interroger des sources externesDetection, segmentation and localization of individual trees from MMS point cloud data / Martin Weinmann (2016)
Titre : Detection, segmentation and localization of individual trees from MMS point cloud data Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Clément Mallet Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2016 Projets : IQmulus / Métral, Claudine Conférence : GEOBIA 2016, 6th international conference on geographic object-based image analysis : Solutions and synergies 14/09/2016 16/09/2016 Enschede Pays-Bas Open Access Proceedings Importance : 9 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Delft (Pays-Bas)
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (auteur) In this paper, we address the extraction of objects from 3D point clouds acquired with mobile mapping systems. More specifically, we focus on the detection of tree-like objects, a subsequent segmentation of individual trees and a localization of the respective trees. Thereby, the detection of tree-like objects is achieved via a binary point-wise classification based on geometric features, which categorizes each point of the 3D point cloud into either tree-like objects or non-tree-like objects. The subsequent segmentation and localization of individual trees is carried out by applying a 2D projection and a mean shift segmentation on a downsampled version of that part of the original 3D point cloud which represents all tree-like objects, and it also involves a segment-based shape analysis to only retain
plausible tree segments. We demonstrate the performance of our framework on a benchmark dataset which contains 10:13M 3D points and has been acquired with a mobile mapping system in the city of Delft in the Netherlands.Numéro de notice : C2016-049 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.3990/2.388 En ligne : https://doi.org/10.3990/2.388 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91899 Documents numériques
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