Descripteur
Termes IGN > sciences naturelles > physique > traitement d'image > lasergrammétrie > traitement de semis de points
traitement de semis de points |
Documents disponibles dans cette catégorie (23)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
A hierarchical multiview registration framework of TLS point clouds based on loop constraint / Hao Wu in ISPRS Journal of photogrammetry and remote sensing, vol 195 (January 2023)
[article]
Titre : A hierarchical multiview registration framework of TLS point clouds based on loop constraint Type de document : Article/Communication Auteurs : Hao Wu, Auteur ; Li Yan, Auteur ; Hong Xie, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 65 - 76 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme ICP
[Termes IGN] appariement de points
[Termes IGN] approche hiérarchique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] graphe
[Termes IGN] recalage d'image
[Termes IGN] semis de points
[Termes IGN] superposition de données
[Termes IGN] traitement de semis de pointsRésumé : (auteur) Automatic registration of multiple point clouds is a significant preprocessing step for 3D computer vision tasks including semantic segmentation, 3D modelling, change detection, etc. Many methods were proposed to deal with this problem and yet most of them are not fully utilizing the redundant information offered by multiple common overlaps among point clouds. The existing methods are also inefficient when dealing with large-scale point clouds. In this paper, a novel automatic registration framework is presented to align point clouds efficiently and robustly. First, the overall number of scans is grouped into several scan-blocks by a proposed blocking strategy, and we build the pairwise relationship among scans through a fully connected graph in each scan-block. Second, perform loop-based coarse registration in each scan-block using a proposed false matches removal strategy. The proposed strategy can effectively identify grossly wrong scan-to-scan matches. Third, the minimum spanning tree is extracted from the graph, and ICP is applied along its edges. Moreover, the Lu–Milios algorithm is used to further optimize all poses at once by utilizing all redundant information in each scan-block. Finally, global block-to-block registration aligns all scan-blocks into a uniform coordinate reference. We test our framework on challenging WHU-TLS datasets, ETH datasets, and Robotic 3D Scan datasets to evaluate the efficiency, accuracy, as well as robustness. The experiment results show that our method achieves the state-of-the-art accuracy, while the time performance is improved by more than 30% compared with the state-of-the-art algorithms. Our source code is made available at https://github.com/WuHao-WHU/HL-MRF for benchmarking purposes. Numéro de notice : A2023-008 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.11.004 Date de publication en ligne : 19/11/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.11.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102112
in ISPRS Journal of photogrammetry and remote sensing > vol 195 (January 2023) . - pp 65 - 76[article]Semantic segmentation of urban textured meshes through point sampling / Grégoire Grzeczkowicz in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)
[article]
Titre : Semantic segmentation of urban textured meshes through point sampling Type de document : Article/Communication Auteurs : Grégoire Grzeczkowicz , Auteur ; Bruno Vallet , Auteur Année de publication : 2022 Projets : 1-Pas de projet / Article en page(s) : pp 177 - 184 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] échantillonnage de données
[Termes IGN] maillage
[Termes IGN] maille carrée
[Termes IGN] maille triangulaire
[Termes IGN] scène urbaine
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] traitement de semis de pointsMots-clés libres : maille texturée (maille qui porte l'information géométrique et radiométrique) Résumé : (auteur) Textured meshes are becoming an increasingly popular representation combining the 3D geometry and radiometry of real scenes. However, semantic segmentation algorithms for urban mesh have been little investigated and do not exploit all radiometric information. To address this problem, we adopt an approach consisting in sampling a point cloud from the textured mesh, then using a point cloud semantic segmentation algorithm on this cloud, and finally using the obtained semantic to segment the initial mesh. In this paper, we study the influence of different parameters such as the sampling method, the density of the extracted cloud, the features selected (color, normal, elevation) as well as the number of points used at each training period. Our result outperforms the state-of-the-art on the SUM dataset, earning about 4 points in OA and 18 points in mIoU. Numéro de notice : A2022-427 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2022-177-2022 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2022-177-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100733
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2022 (2022 edition) . - pp 177 - 184[article]Point clouds for use in Building Information Models (BIM) / Robert Klinc in Geodetski vestnik, vol 65 n° 4 (December 2021 - February 2022)
[article]
Titre : Point clouds for use in Building Information Models (BIM) Type de document : Article/Communication Auteurs : Robert Klinc, Auteur ; Uroš Jotanović, Auteur ; Klemen Kregar, Auteur Année de publication : 2021 Article en page(s) : pp 594 - 613 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canalisation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction automatique
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] mur
[Termes IGN] qualité du modèle
[Termes IGN] Revit
[Termes IGN] semis de points
[Termes IGN] traitement de semis de pointsRésumé : (Auteur) The use of point clouds in extracting data for building information modelling (BIM) has become common recently. Managers of older buildings are working to centralise information. Documentation about mechanical installations, plumbing, electricity, and previous interventions is often stored on scattered media, frequently still on paper. In the transformation of the material world into the digital world, the point cloud is the starting point, containing information about the material world obtained by various means such as photogrammetry, terrestrial or aerial laser scanning. Manual BIM modelling for management, maintenance and future use is a time-consuming and error-prone process. We would like to automate this process and avoid these errors. Recently, there have been developed an increasing number of stand-alone programmes and add-ons that provide automated, fast, and more accurate modelling based on point cloud data. In this paper, we present an investigation into the possibilities for automating the creation of BIM models from point cloud data. The result is a semi-automated process for modelling individual BIM elements, which we have tested on specific examples of modelling individual elements (walls, pipes, and columns). We note that despite the automation of the process, a high level of user interaction is still required to produce good quality models. Numéro de notice : A2021-931 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.15292/geodetski-vestnik.2021.04.594-613 Date de publication en ligne : 06/12/2021 En ligne : https://doi.org/10.15292/geodetski-vestnik.2021.04.594-613 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99410
in Geodetski vestnik > vol 65 n° 4 (December 2021 - February 2022) . - pp 594 - 613[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 139-2021041 RAB Revue Centre de documentation En réserve L003 Disponible Development of German-Ukrainian cooperations for education and research in photogrammetry and laser scanning / Thomas Luhmann in Geo-spatial Information Science, vol 24 n° 1 (March 2021)
[article]
Titre : Development of German-Ukrainian cooperations for education and research in photogrammetry and laser scanning Type de document : Article/Communication Auteurs : Thomas Luhmann, Auteur Année de publication : 2021 Article en page(s) : pp 152 - 159 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Formation
[Termes IGN] Allemagne
[Termes IGN] apprentissage en ligne
[Termes IGN] balayage laser
[Termes IGN] coopération internationale
[Termes IGN] enseignement supérieur
[Termes IGN] formation à distance
[Termes IGN] modélisation 3D
[Termes IGN] photogrammétrie
[Termes IGN] recherche scientifique
[Termes IGN] semis de points
[Termes IGN] traitement de semis de points
[Termes IGN] UkraineRésumé : (Auteur) Since 2011 an intensive international cooperation has been in place between the Institute for Applied Photogrammetry and Geoinformatics (IAPG) at the Jade University of Applied Sciences in Oldenburg, Germany, and various Ukrainian universities. Following an initial contact by Prof. Gottfried Konecny, the first visit was organized, and was followed by many more. In subsequent years an intensive cooperation was established particularly with the National University for Construction and Architecture (KNUCA) in Kiev. In addition to architects and civil engineers, KNUCA also trains geodesists, geo-information scientists and landscape planners. The cooperation today includes the reciprocal exchange of scientists and students, research projects, courses and cooperation at many other levels. In addition, a commercial company has been established, SPM3D LLC, which now employs more than 14 engineers in the field of 3D acquisition, point cloud processing and modeling. This article summarizes the history of the cooperation and presents the results of associated student projects. In addition, results of joint work on the development of a virtual laser scanner are presented, part of a German-Ukrainian initiative to digitize teaching. Numéro de notice : A2021-299 Affiliation des auteurs : non IGN Thématique : IMAGERIE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1831891 Date de publication en ligne : 13/10/2020 En ligne : https://doi.org/10.1080/10095020.2020.1831891 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97384
in Geo-spatial Information Science > vol 24 n° 1 (March 2021) . - pp 152 - 159[article]
Titre : Benefiting from local rigidity in 3D point cloud processing Type de document : Thèse/HDR Auteurs : Zan Gojcic, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2021 Importance : 141 p. Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of Doctor of Sciences of ETH ZurichLangues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] capteur actif
[Termes IGN] champ vectoriel
[Termes IGN] déformation d'image
[Termes IGN] données lidar
[Termes IGN] effondrement de terrain
[Termes IGN] enregistrement de données
[Termes IGN] filtrage du bruit
[Termes IGN] flux
[Termes IGN] image 3D
[Termes IGN] navigation autonome
[Termes IGN] orientation du capteur
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] téléphone intelligent
[Termes IGN] traitement de semis de points
[Termes IGN] voxelIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Incorporating 3D understanding and spatial reasoning into (intelligent) algorithms is crucial for solving several tasks in fields such as engineering geodesy, risk assessment, and autonomous driving. Humans are capable of reasoning about 3D spatial relations even from a single 2D image. However, making the priors that we rely on explicit and integrating them into computer programs is very challenging. Operating directly on 3D input data, such as 3D point clouds, alleviates the need to lift 2D data into a 3D representation within the task-specific algorithm and hence reduces the complexity of the problem. The 3D point clouds are not only a better-suited input data representation, but they are also becoming increasingly easier to acquire. Indeed, nowadays, LiDAR sensors are even integrated into consumer devices such as mobile phones. However, these sensors often have a limited field of view, and hence multiple acquisitions are required to cover the whole area of interest. Between these acquisitions, the sensor has to be moved and pointed in a different direction. Moreover, the world that surrounds us is also dynamic and might change as well. Reasoning about the motion of both the sensor and the environment, based on point clouds acquired in two-time steps, is therfore an integral part of point cloud processing. This thesis focuses on incorporating rigidity priors into novel deep learning based approaches for dynamic 3D perception from point cloud data. Specifically, the tasks of point cloud registration, deformation analysis, and scene flow estimation are studied. At first, these tasks are incorporated into a common framework where the main difference is in the level of rigidity assumptions that are imposed on the motion of the scene or
the acquisition sensor. Then, the tasks specific priors are proposed and incorporated into novel deep learning architectures. While the global rigidity can be assumed in point cloud registration, the motion patterns in deformation analysis and scene flow estimation are more complex. Therefore, the global rigidity prior has to be relaxed to local or instancelevel rigidity, respectively. Rigidity priors not only add structure to the aforementioned tasks, which prevents physically implausible estimates and improves the generalization of the algorithms, but in some cases also reduce the supervision requirements. The proposed approaches were quantitatively and qualitatively evaluated on several datasets, and they yield favorable performance compared to the state-of-the-art.Numéro de notice : 28660 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD : Sciences : ETH Zurich : 2021 DOI : sans En ligne : https://www.research-collection.ethz.ch/handle/20.500.11850/523368 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99817 Correction radiométrique et recalage de nuages de points pour la reconstruction tridimensionnelle d'oeuvres du patrimoine culturel / Nathan Sanchiz (2021)PermalinkPlanar polygons detection in lidar scans based on sensor topology enhanced Ransac / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkProvably consistent distributed Delaunay triangulation / Mathieu Brédif in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkDirectionally constrained fully convolutional neural network for airborne LiDAR point cloud classification / Congcong Wen in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)PermalinkCartographie sémantique hybride de scènes urbaines à partir de données image et Lidar / Mohamed Boussaha (2020)PermalinkDe l’image optique "multi-stéréo" à la topographie très haute résolution et la cartographie automatique des failles par apprentissage profond / Lionel Matteo (2020)PermalinkReview of mobile laser scanning target‐free registration methods for urban areas using improved error metrics / Hoang Long Nguyen in Photogrammetric record, vol 34 n° 167 (September 2019)PermalinkRelevé de la grotte glacée de Cenote Abyss dans les Dolomites / Farouk Kadded in XYZ, n° 157 (décembre 2018 - février 2019)PermalinkSuivi et conservation du patrimoine historique et culturel / Jocelyn Le Maître (2018)PermalinkA review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures / Wallace Mukupa in Survey review, vol 49 n° 353 (June 2017)Permalink