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Provably consistent distributed Delaunay triangulation / Mathieu Brédif in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 195 - 202 Titre : Provably consistent distributed Delaunay triangulation Type de document : Article/Communication Auteurs : Mathieu Brédif , Auteur ; Laurent Caraffa , Auteur ; Murat Yirci, Auteur ; Pooran Memari, Auteur Année de publication : 2020 Projets : IQmulus / Métral, Claudine Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 195 - 202 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] géomètrie algorithmique [Termes IGN] informatique en nuage [Termes IGN] semis de points [Termes IGN] Spark [Termes IGN] traitement de semis de points [Termes IGN] triangulation de Delaunay Résumé : (Auteur) This paper deals with the distributed computation of Delaunay triangulations of massive point sets, mainly motivated by the needs of a scalable out-of-core surface reconstruction workflow from massive urban LIDAR datasets. Such a data often corresponds to a huge point cloud represented through a set of tiles of relatively homogeneous point sizes. This will be the input of our algorithm which will naturally partition this data across multiple processing elements. The distributed computation and communication between processing elements is orchestrated efficiently through an uncentralized model to represent, manage and locally construct the triangulation corresponding to each tile. Initially inspired by the star splaying approach, we review the Tile\& Merge algorithm for computing Distributed Delaunay Triangulations on the cloud, provide a theoretical proof of correctness of this algorithm, and analyse the performance of our Spark implementation in terms of speedup and strong scaling in both synthetic and real use case datasets. A HPC implementation (e.g. using MPI), left for future work, would benefit from its more efficient message passing paradigm but lose the robustness and failure resilience of our Spark approach. Numéro de notice : A2020-410 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-195-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-195-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94979 [article]

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]

3D watertight mesh generation with uncertainties from ubiquitous data / Laurent Caraffa (2016)    

Public Titre : 3D watertight mesh generation with uncertainties from ubiquitous data Type de document : Article/Communication Auteurs : Laurent Caraffa , Auteur ; Mathieu Brédif , Auteur ; Bruno Vallet , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2016 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 10114 Projets : IQmulus / Métral, Claudine Conférence : ACCV 2016, 13th Asian Conference on Computer Vision 20/11/2016 24/11/2016 Taipei Taiwan Proceedings Springer Importance : pp 377 - 391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] algorithme Graph-Cut [Termes IGN] carte de confiance [Termes IGN] distance de Hausdorff [Termes IGN] incertitude géométrique [Termes IGN] maille triangulaire [Termes IGN] reconstruction d'objet [Termes IGN] semis de points [Termes IGN] seuillage [Termes IGN] surface imperméable [Termes IGN] théorie de Dempster-Shafer Résumé : (auteur) In this paper, we propose a generic framework for watertight mesh generation with uncertainties that provides a confidence measure on each reconstructed mesh triangle. Its input is a set of vision-based or Lidar-based 3D measurements which are converted to a set of mass functions that characterize the level of confidence on the occupancy of the scene as occupied, empty or unknown based on Dempster-Shafer Theory. The output is a multi-label segmentation of the ambient 3D space expressing the confidence for each resulting volume element to be occupied or empty. While existing methods either sacrifice watertightness (local methods) or need to introduce a smoothness prior (global methods), we derive a per-triangle confidence measure that is able to gradually characterize when the resulting surface patches are certain due to dense and coherent measurements and when these patches are more uncertain and are mainly present to ensure smoothness and/or watertightness. The surface mesh reconstruction is formulated as a global energy minimization problem efficiently optimized with the α-expansion algorithm. We claim that the resulting confidence measure is a good estimate of the local lack of sufficiently dense and coherent input measurements, which would be a valuable input for the next-best-view scheduling of a complementary acquisition. Beside the new formulation, the proposed approach achieves state-of-the-art results on surface reconstruction benchmark. It is robust to noise, manages high scale disparity and produces a watertight surface with a small Hausdorff distance in uncertainty area thanks to the multi-label formulation. By simply thresholding the result, the method shows a good reconstruction quality compared to local algorithms on high density data. This is demonstrated on a large scale reconstruction combining real-world datasets from airborne and terrestrial Lidar and on an indoor scene reconstructed from images. Numéro de notice : C2016-024 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-319-54190-7_23 Date de publication en ligne : 12/03/2017 En ligne : http://doi.org/10.1007/978-3-319-54190-7_23 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84627

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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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en open access Detection, segmentation... - pdf auteur Adobe Acrobat PDF

Segmentation and localization of individual trees from MMS point cloud data acquired in urban areas / Martin Weinmann (2016)    

Public Titre : Segmentation and localization of individual trees from MMS point cloud data acquired in urban areas Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Clément Mallet , Auteur ; Mathieu Brédif , Auteur Editeur : Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation Année de publication : 2016 Collection : Tagungsbände, ISSN 0942-2870 num. 25 Projets : IQmulus / Métral, Claudine Conférence : DGPF 2016, 36. Wissenschaftlich-Technische Jahrestagung der DGPF, Dreiländertagung der SGPF, DGPF und OVG Lösungen für eine Welt im Wandel 07/06/2016 09/06/2016 Bern Suisse OA Proceedings Importance : pp 351 - 360 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre urbain [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] zone urbaine Résumé : (auteur) In this paper, we address tree segmentation and localization in the scope of the IQmulus Processing Contest IQPC’15. Based on the part of pre-classified 3D point cloud data which corresponds to trees, we present a novel framework which involves a downsampling of the original data, a projection of the downsampled data onto a horizontally oriented plane, a mean-shift-based segmentation of the projected points, a transfer of the segmentation results to the original data, a refinement of the segmentation results via segment-based shape analysis, and a localization of respective tree trunks. The results derived for a benchmark dataset reveal that all individual trees are correctly detected and localized with both acceptable accuracy and reasonable computational effort. Numéro de notice : C2016-061 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésNat DOI : sans En ligne : https://www.dgpf.de/src/tagung/jt2016/start.html Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91920

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peut être téléchargé Segmentation and localization... - pdf auteur Adobe Acrobat PDF

The iQmulus urban showcase: automatic tree classification and identification in huge mobile mapping point clouds / Jan Böhm (2016)    

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TerraMobilita/iQmulus urban point cloud analysis benchmark / Bruno Vallet in Computers and graphics, vol 49 (June 2015)  

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