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Single tree detection from airborne laser scanning data using a marked point process based method / Junjie Zhang in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W1 (May 2013)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W1 (May 2013) . - pp 41 - 46 Titre : Single tree detection from airborne laser scanning data using a marked point process based method Type de document : Article/Communication Auteurs : Junjie Zhang, Auteur ; Gunho Sohn, Auteur ; Mathieu Brédif , Auteur Année de publication : 2013 Conférence : ISPRS VCM 2013, ISPRS Workshop on 3D Virtual City Modeling 28/05/2013 25/05/2013 Regina Saskatchewan - Canada OA ISPRS Annals Article en page(s) : pp 41 - 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme du gradient [Termes IGN] arbre (flore) [Termes IGN] détection d'objet [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] enthalpie libre [Termes IGN] forêt [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] placette d'échantillonnage [Termes IGN] programmation par contraintes [Termes IGN] reconstruction d'objet Mots-clés libres : Single tree detection  marked point process  segmentation Résumé : (auteur) Tree detection and reconstruction is of great interest in large-scale city modelling. In this paper, we present a marked point process model to detect single trees from airborne laser scanning (ALS) data. We consider single trees in ALS recovered canopy height model (CHM) as a realization of point process of circles. Unlike traditional marked point process, we sample the model in a constraint configuration space by making use of image process techniques. A Gibbs energy is defined on the model, containing a data term which judge the fitness of the model with respect to the data, and prior term which incorporate the prior knowledge of object layouts. We search the optimal configuration through a steepest gradient descent algorithm. The presented hybrid framework was test on three forest plots and experiments show the effectiveness of the proposed method. Numéro de notice : A2013-821 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W1-41-2013 Date de publication en ligne : 16/05/2013 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W1-41-2013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80995 [article]