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Termes IGN > 1-Candidats > semis de points
semis de points
Commentaire :
- Ensemble de points répartis de façon régulière ou quelconque sur une zone géographique donnée. (Glossaire de cartographie / CFC) Ces points peuvent être issus d'images ou de données lidar ...
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Piecewise-planar approximation of large 3D data as graph-structured optimization / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2/W5 (May 2019)
[article]
Titre : Piecewise-planar approximation of large 3D data as graph-structured optimization Type de document : Article/Communication Auteurs : Stéphane Guinard , Auteur ; Loïc Landrieu , Auteur ; Laurent Caraffa , Auteur ; Bruno Vallet , Auteur Année de publication : 2019 Projets : 1-Pas de projet / Conférence : ISPRS 2019, Geospatial Week 10/06/2019 14/06/2019 Enschede Pays-Bas ISPRS OA Annals Article en page(s) : pp 365 - 372 Note générale : bibliographie
The authors would like to acknowledge the DGA for their financial support of this work.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de décalage moyen
[Termes IGN] analyse de groupement
[Termes IGN] approximation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] érosion anthropique
[Termes IGN] erreur d'approximation
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] graphe
[Termes IGN] maillage
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de points
[Termes IGN] surface planeRésumé : (auteur) We introduce a new method for the piecewise-planar approximation of 3D data, including point clouds and meshes. Our method is designed to operate on large datasets (e.g. millions of vertices) containing planar structures, which are very frequent in anthropic scenes. Our approach is also adaptive to the local geometric complexity of the input data. Our main contribution is the formulation of the piecewise-planar approximation problem as a non-convex optimization problem. In turn, this problem can be efficiently solved with a graph-structured working set approach. We compare our results with a state-of-the-art region-growing-based segmentation method and show a significant improvement both in terms of approximation error and computation efficiency. Numéro de notice : A2019-592 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-IV-2-W5-365-2019 Date de publication en ligne : 29/05/2019 En ligne : https://doi.org/10.5194/isprs-annals-IV-2-W5-365-2019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94552
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-2/W5 (May 2019) . - pp 365 - 372[article]On the positional accuracy and maximum allowable scale of UAV-derived photogrammetric products for archaeological site documentation / Juan Antonio Pérez in Geocarto international, vol 34 n° 6 ([15/05/2019])
[article]
Titre : On the positional accuracy and maximum allowable scale of UAV-derived photogrammetric products for archaeological site documentation Type de document : Article/Communication Auteurs : Juan Antonio Pérez, Auteur ; Gil Rito-Gonçalves , Auteur ; Maria Cristina Charro, Auteur Année de publication : 2019 Article en page(s) : pp 575 - 585 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] chaîne de traitement
[Termes IGN] échelle de prise de vue
[Termes IGN] Espagne
[Termes IGN] image captée par drone
[Termes IGN] modèle 3D du site
[Termes IGN] modèle numérique de surface
[Termes IGN] orthoimage
[Termes IGN] précision du positionnement
[Termes IGN] semis de points
[Termes IGN] site archéologiqueRésumé : (Auteur) Blending photogrammetric and Structure from Motion techniques with Unmanned Aerial Vehicles (UAV) is a commonly used approach for the documentation and analysis of archaeological sites. Using the dense 3D point clouds generated from these techniques, two main photogrammetric products are created: orthophotos and Digital Surfaces Models (DSM). Depending on the UAV technology, the flight parameters, the topography and land cover of the flown area, DSMs and orthophotos are delivered with varying positional accuracies and output scales. In this paper, the positional accuracy and maximum allowable scale of these products generated by complete automation of flight mode and processing workflow are assessed. Moreover, three known International Mapping Standards (IMS) are validated using independent checkpoints, obtained by geodetic Global Navigation Satellite Systems receivers, in two Spanish study areas. The results show that accurate photogrammetric products adapted to the IMS can be successfully obtained by the automation of the photogrammetric workflow. Numéro de notice : A2019-453 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1421714 Date de publication en ligne : 09/01/2018 En ligne : https://doi.org/10.1080/10106049.2017.1421714 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92841
in Geocarto international > vol 34 n° 6 [15/05/2019] . - pp 575 - 585[article]Automatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network / Jianfeng Huang in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
[article]
Titre : Automatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network Type de document : Article/Communication Auteurs : Jianfeng Huang, Auteur ; Xinchang Zhang, Auteur ; Qinchuan Xin, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 91 - 105 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] détection du bâti
[Termes IGN] image à haute résolution
[Termes IGN] réseau neuronal convolutif
[Termes IGN] résidu
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (Auteur) Automated extraction of buildings from remotely sensed data is important for a wide range of applications but challenging due to difficulties in extracting semantic features from complex scenes like urban areas. The recently developed fully convolutional neural networks (FCNs) have shown to perform well on urban object extraction because of the outstanding feature learning and end-to-end pixel labeling abilities. The commonly used feature fusion or skip-connection refine modules of FCNs often overlook the problem of feature selection and could reduce the learning efficiency of the networks. In this paper, we develop an end-to-end trainable gated residual refinement network (GRRNet) that fuses high-resolution aerial images and LiDAR point clouds for building extraction. The modified residual learning network is applied as the encoder part of GRRNet to learn multi-level features from the fusion data and a gated feature labeling (GFL) unit is introduced to reduce unnecessary feature transmission and refine classification results. The proposed model - GRRNet is tested in a publicly available dataset with urban and suburban scenes. Comparison results illustrated that GRRNet has competitive building extraction performance in comparison with other approaches. The source code of the developed GRRNet is made publicly available for studies. Numéro de notice : A2019-206 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.019 Date de publication en ligne : 20/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92669
in ISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 91 - 105[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019051 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019053 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019052 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Automatic reconstruction of fully volumetric 3D building models from oriented point clouds / Sebastian Ochmann in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
[article]
Titre : Automatic reconstruction of fully volumetric 3D building models from oriented point clouds Type de document : Article/Communication Auteurs : Sebastian Ochmann, Auteur ; Richard Vock, Auteur ; Reinhard Klein, Auteur Année de publication : 2019 Article en page(s) : pp 251 - 262 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] format Industry foudation classes IFC
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] positionnement en intérieur
[Termes IGN] programmation linéaire
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] semis de pointsRésumé : (Auteur) We present a novel method for reconstructing parametric, volumetric, multi-story building models from unstructured, unfiltered indoor point clouds with oriented normals by means of solving an integer linear optimization problem. Our approach overcomes limitations of previous methods in several ways: First, we drop assumptions about the input data such as the availability of separate scans as an initial room segmentation. Instead, a fully automatic room segmentation and outlier removal is performed on the unstructured point clouds. Second, restricting the solution space of our optimization approach to arrangements of volumetric wall entities representing the structure of a building enforces a consistent model of volumetric, interconnected walls fitted to the observed data instead of unconnected, paper-thin surfaces. Third, we formulate the optimization as an integer linear programming problem which allows for an exact solution instead of the approximations achieved with most previous techniques. Lastly, our optimization approach is designed to incorporate hard constraints which were difficult or even impossible to integrate before. We evaluate and demonstrate the capabilities of our proposed approach on a variety of complex real-world point clouds. Numéro de notice : A2019-210 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.017 Date de publication en ligne : 30/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.017 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92676
in ISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 251 - 262[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019051 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019053 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019052 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Detecting and characterizing downed dead wood using terrestrial laser scanning / Tuomas Yrttimaa in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
[article]
Titre : Detecting and characterizing downed dead wood using terrestrial laser scanning Type de document : Article/Communication Auteurs : Tuomas Yrttimaa, Auteur ; Ninni Saarinen, Auteur ; Ville Luoma, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 76 - 90 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] bois mort
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] placette d'échantillonnage
[Termes IGN] qualité des données
[Termes IGN] Ransac (algorithme)
[Termes IGN] rastérisation
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] tronc
[Termes IGN] volume en boisRésumé : (Auteur) Dead wood is a key forest structural component for maintaining biodiversity and storing carbon. Despite its important role in a forest ecosystem, quantifying dead wood alongside standing trees has often neglected when investigating the feasibility of terrestrial laser scanning (TLS) in forest inventories. The objective of this study was therefore to develop an automatic method for detecting and characterizing downed dead wood with a diameter exceeding 5 cm using multi-scan TLS data. The developed four-stage algorithm included (1) RANSAC-cylinder filtering, (2) point cloud rasterization, (3) raster image segmentation, and (4) dead wood trunk positioning. For each detected trunk, geometry-related quality attributes such as dimensions and volume were automatically determined from the point cloud. For method development and validation, reference data were collected from 20 sample plots representing diverse southern boreal forest conditions. Using the developed method, the downed dead wood trunks were detected with an overall completeness of 33% and correctness of 76%. Up to 92% of the downed dead wood volume were detected at plot level with mean value of 68%. We were able to improve the detection accuracy of individual trunks with visual interpretation of the point cloud, in which case the overall completeness was increased to 72% with mean proportion of detected dead wood volume of 83%. Downed dead wood volume was automatically estimated with an RMSE of 15.0 m3/ha (59.3%), which was reduced to 6.4 m3/ha (25.3%) as visual interpretation was utilized to aid the trunk detection. The reliability of TLS-based dead wood mapping was found to increase as the dimensions of dead wood trunks increased. Dense vegetation caused occlusion and reduced the trunk detection accuracy. Therefore, when collecting the data, attention must be paid to the point cloud quality. Nevertheless, the results of this study strengthen the feasibility of TLS-based approaches in mapping biodiversity indicators by demonstrating an improved performance in quantifying ecologically most valuable downed dead wood in diverse forest conditions. Numéro de notice : A2019-205 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.007 Date de publication en ligne : 16/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92668
in ISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 76 - 90[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019051 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019053 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019052 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Digital surface model generation from high resolution multi-view stereo satellite imagery / Ke Gong in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 5 (May 2019)PermalinkEstimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling / Alvaro Lau in Forest ecology and management, vol 439 (1 May 2019)PermalinkFusion of thermal imagery with point clouds for building façade thermal attribute mapping / Dong Lin in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkPairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets / Yusheng Xu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkVoxel-based 3D point cloud semantic segmentation: unsupervised geometric and relationship featuring vs deep learning methods / Florent Poux in ISPRS International journal of geo-information, vol 8 n° 5 (May 2019)PermalinkJournées de la recherche 2019 / Anonyme in Géomatique expert, n° 127 (avril - mai 2019)PermalinkLearning high-level features by fusing multi-view representation of MLS point clouds for 3D object recognition in road environments / Zhipeng Luo in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)PermalinkOrléans monte sa maquette virtuelle / Anonyme in Géomatique expert, n° 127 (avril - mai 2019)PermalinkRobust external calibration of terrestrial laser scanner and digital camera for structural monitoring / Mohammad Omidalizarandi in Journal of applied geodesy, vol 13 n° 2 (April 2019)Permalink3D hyperspectral point cloud generation: Fusing airborne laser scanning and hyperspectral imaging sensors for improved object-based information extraction / Maximilian Brell in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)Permalink