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A classification-segmentation framework for the detection of individual trees in dense MMS point cloud data acquired in urban areas / Martin Weinmann in Remote sensing, vol 9 n° 3 (March 2017)  

Public [article]  inRemote sensing > vol 9 n° 3 (March 2017) . - pp 277 Titre : A classification-segmentation framework for the detection of individual trees in dense MMS point cloud data acquired in urban areas Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Michael Weinmann, Auteur ; Clément Mallet , Auteur ; Mathieu Brédif , Auteur Année de publication : 2017 Projets : IQmulus / Métral, Claudine Article en page(s) : pp 277 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme de décalage moyen [Termes IGN] arbre (flore) [Termes IGN] classification [Termes IGN] Delft (Pays-Bas) [Termes IGN] détection d'objet [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] voxel [Termes IGN] zone urbaine Résumé : (auteur) In this paper, we present a novel framework for detecting individual trees in densely sampled 3D point cloud data acquired in urban areas. Given a 3D point cloud, the objective is to assign point-wise labels that are both class-aware and instance-aware, a task that is known as instance-level segmentation. To achieve this, our framework addresses two successive steps. The first step of our framework is given by the use of geometric features for a binary point-wise semantic classification with the objective of assigning semantic class labels to irregularly distributed 3D points, whereby the labels are defined as “tree points” and “other points”. The second step of our framework is given by a semantic segmentation with the objective of separating individual trees within the “tree points”. This is achieved by applying an efficient adaptation of the mean shift algorithm and a subsequent segment-based shape analysis relying on semantic rules to only retain plausible tree segments. We demonstrate the performance of our framework on a publicly available benchmark dataset, which has been acquired with a mobile mapping system in the city of Delft in the Netherlands. This dataset contains 10.13 M labeled 3D points among which 17.6 % are labeled as “tree points”. The derived results clearly reveal a semantic classification of high accuracy (up to 90.77 %) and an instance-level segmentation of high plausibility, while the simplicity, applicability and efficiency of the involved methods even allow applying the complete framework on a standard laptop computer with a reasonable processing time (less than 2.5 h) Numéro de notice : A2017-140 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs9030277 Date de publication en ligne : 16/03/2017 En ligne : http://doi.org/10.3390/rs9030277 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84614 [article]

Detection, segmentation and localization of individual trees from MMS point cloud data / Martin Weinmann (2016)    

Public Titre : Detection, segmentation and localization of individual trees from MMS point cloud data Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Clément Mallet , Auteur ; Mathieu Brédif , Auteur 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 points Résumé : (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

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Semantically enriching point clouds / Merwin Rook in GIM international, vol 30 n° 1 (January 2016)

Public [article]  inGIM international > vol 30 n° 1 (January 2016) . - pp 31 - 33 Titre : Semantically enriching point clouds Type de document : Article/Communication Auteurs : Merwin Rook, Auteur ; Stella Psomadaki, Auteur Année de publication : 2016 Article en page(s) : pp 31 - 33 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] acquisition de données [Termes IGN] application métier [Termes IGN] Delft (Pays-Bas) [Termes IGN] formation [Termes IGN] information géographique [Termes IGN] traitement de données Résumé : (éditeur) The Geomatics master programme at Delft University of Technology focuses on geographical information science. Geomatics in Delft differs from other geomatics programmes in its close connection to the Faculty of Architecture and the Built Environment. In their second - and final - year of study, the geomatics students embarked on a 10-week Geomatics Synthesis Project as a group. The objective was to undertake a small but real-world research project where experience could be gained in the entire geoinformatics chain (acquisition, processing and application). Numéro de notice : A2016-016 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79348 [article]

The Kootwijk observatory, for satellite geodesy laser ranging contributions to international programs / L. Aardoom in Surveying and Mapping, vol 44 n° 4 (Winter 1984)

Public [article]  inSurveying and Mapping > vol 44 n° 4 (Winter 1984) . - pp 353 - 363 Titre : The Kootwijk observatory, for satellite geodesy laser ranging contributions to international programs Type de document : Article/Communication Auteurs : L. Aardoom, Auteur Année de publication : 1984 Article en page(s) : pp 353 - 363 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] Delft (Pays-Bas) [Termes IGN] nivellement direct [Termes IGN] observatoire astronomique [Termes IGN] observatoire scientifique [Termes IGN] repère de nivellement [Termes IGN] satellite d'observation de la mer [Termes IGN] télémétrie laser sur satellite Numéro de notice : A1984-016 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83631 [article]

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