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City3D: Large-scale building reconstruction from airborne LiDAR point clouds / Jin Huang in Remote sensing, vol 14 n° 9 (May-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 9 (May-1 2022) . - n° 2254 Titre : City3D: Large-scale building reconstruction from airborne LiDAR point clouds Type de document : Article/Communication Auteurs : Jin Huang, Auteur ; Jantien E. Stoter, Auteur ; Ravi Peters, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 2254 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] empreinte [Termes IGN] mur [Termes IGN] polygonale [Termes IGN] primitive géométrique [Termes IGN] reconstruction 3D du bâti [Termes IGN] semis de points [Termes IGN] toit [Termes IGN] Triangular Regular Network [Termes IGN] triangulation de Delaunay Résumé : (auteur) We present a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. A major challenge of urban reconstruction from airborne LiDAR point clouds lies in that the vertical walls are typically missing. Based on the observation that urban buildings typically consist of planar roofs connected with vertical walls to the ground, we propose an approach to infer the vertical walls directly from the data. With the planar segments of both roofs and walls, we hypothesize the faces of the building surface, and the final model is obtained by using an extended hypothesis-and-selection-based polygonal surface reconstruction framework. Specifically, we introduce a new energy term to encourage roof preferences and two additional hard constraints into the optimization step to ensure correct topology and enhance detail recovery. Experiments on various large-scale airborne LiDAR point clouds have demonstrated that the method is superior to the state-of-the-art methods in terms of reconstruction accuracy and robustness. In addition, we have generated a new dataset with our method consisting of the point clouds and 3D models of 20k real-world buildings. We believe this dataset can stimulate research in urban reconstruction from airborne LiDAR point clouds and the use of 3D city models in urban applications. Numéro de notice : A2022-387 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.3390/rs14092254 Date de publication en ligne : 07/05/2022 En ligne : https://doi.org/10.3390/rs14092254 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100667 [article]

Automated 3D reconstruction of LoD2 and LoD1 models for All 10 million buildings of the Netherlands / Ravi Peters in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 3 (March 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 3 (March 2022) . - pp 165 - 170 Titre : Automated 3D reconstruction of LoD2 and LoD1 models for All 10 million buildings of the Netherlands Type de document : Article/Communication Auteurs : Ravi Peters, Auteur ; Balazs Dukai, Auteur ; Stelios Vitalis, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 165 - 170 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] données lidar [Termes IGN] empreinte [Termes IGN] itération [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] niveau de détail [Termes IGN] Pays-Bas [Termes IGN] qualité des données [Termes IGN] reconstruction 3D du bâti [Termes IGN] toit [Termes IGN] Web Map Tile Service Résumé : (auteur) In this paper, we present our workflow to automatically reconstruct three-dimensional (3D) building models based on two-dimensional building polygons and a lidar point cloud. The workflow generates models at different levels of detail (LoDs) to support data requirements of different applications from one consistent source. Specific attention has been paid to make the workflow robust to quickly run a new iteration in case of improvements in an algorithm or in case new input data become available. The quality of the reconstructed data highly depends on the quality of the input data and is monitored in several steps of the process. A 3D viewer has been developed to view and download the openly available 3D data at different LoDs in different formats. The workflow has been applied to all 10 million buildings of the Netherlands. The 3D service will be updated after new input data becomes available. Numéro de notice : A2022-200 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00032R2 Date de publication en ligne : 01/03/2022 En ligne : https://doi.org/10.14358/PERS.21-00032R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100002 [article]

Utilisation de l’apprentissage profond dans la modélisation 3D urbaine : partie 2, post-traitement et évaluation / Hamza Ben Addou in Géomatique expert, n° 136 (novembre - décembre 2021)

Public [article]  inGéomatique expert > n° 136 (novembre - décembre 2021) . - pp 42 -47 Titre : Utilisation de l’apprentissage profond dans la modélisation 3D urbaine : partie 2, post-traitement et évaluation Type de document : Article/Communication Auteurs : Hamza Ben Addou, Auteur Année de publication : 2021 Article en page(s) : pp 42 -47 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme d'apprentissage [Termes IGN] apprentissage profond [Termes IGN] CityGML [Termes IGN] classification automatique d'objets [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] emprise au sol [Termes IGN] maquette numérique [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle numérique du bâti [Termes IGN] modélisation 3D [Termes IGN] niveau de détail [Termes IGN] orthoimage [Termes IGN] primitive géométrique [Termes IGN] toit Résumé : (Auteur) Post-traitement des données issues de l’algorithme d’apprentissage profond et modélisation 3D urbaine automatique Numéro de notice : A2021-919 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/11/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99335 [article]

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IFN-001-P002286	PER	Revue	Nogent-sur-Vernisson	Salle périodiques	Exclu du prêt

A deep multi-modal learning method and a new RGB-depth data set for building roof extraction / Mehdi Khoshboresh Masouleh in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 10 (October 2021) . - pp 759 - 766 Titre : A deep multi-modal learning method and a new RGB-depth data set for building roof extraction Type de document : Article/Communication Auteurs : Mehdi Khoshboresh Masouleh, Auteur ; Reza Shah-Hosseini, Auteur Année de publication : 2021 Article en page(s) : pp 759 - 766 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage automatique [Termes IGN] détection du bâti [Termes IGN] données multisources [Termes IGN] effet de profondeur cinétique [Termes IGN] empreinte [Termes IGN] extraction automatique [Termes IGN] extraction de traits caractéristiques [Termes IGN] image RVB [Termes IGN] Indiana (Etats-Unis) [Termes IGN] réseau neuronal convolutif [Termes IGN] réseau neuronal profond [Termes IGN] segmentation d'image [Termes IGN] superpixel [Termes IGN] toit Résumé : (Auteur) This study focuses on tackling the challenge of building mapping in multi-modal remote sensing data by proposing a novel, deep superpixel-wise convolutional neural network called DeepQuantized-Net, plus a new red, green, blue (RGB)-depth data set named IND. DeepQuantized-Net incorporated two practical ideas in segmentation: first, improving the object pattern with the exploitation of superpixels instead of pixels, as the imaging unit in DeepQuantized-Net. Second, the reduction of computational cost. The generated data set includes 294 RGB-depth images (256 training images and 38 test images) from different locations in the state of Indiana in the U.S., with 1024 × 1024 pixels and a spatial resolution of 0.5 ftthat covers different cities. The experimental results using the IND data set demonstrates the mean F1 scores and the average Intersection over Union scores could increase by approximately 7.0% and 7.2% compared to other methods, respectively. Numéro de notice : A2021-677 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00007R2 Date de publication en ligne : 01/10/2021 En ligne : https://doi.org/10.14358/PERS.21-00007R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98878 [article]

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Linear regression and lines intersecting as a method of extracting punctual entities in a lidar point cloud / Marlo Antonio Ribeiro Martins in Boletim de Ciências Geodésicas, vol 27 n° 3 ([01/10/2021])  

Public [article]  inBoletim de Ciências Geodésicas > vol 27 n° 3 [01/10/2021] . - 21 p. Titre : Linear regression and lines intersecting as a method of extracting punctual entities in a lidar point cloud Type de document : Article/Communication Auteurs : Marlo Antonio Ribeiro Martins, Auteur ; Edson Aparecido Mitishita, Auteur Année de publication : 2021 Article en page(s) : 21 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] intersection spatiale [Termes IGN] régression linéaire [Termes IGN] semis de points [Termes IGN] toit Résumé : (auteur) The characteristics of data points obtained by laser scanning (LiDAR) and images have been considered complementary in the field of photogrammetric applications, and research to improve their integrated use have recently intensified. This study aim to verify the performance of determining punctual entities in a LiDAR point cloud using linear regression and intersecting lines obtained from buildings with square rooftop containing four planes (hip roof), as well as compare punctual entities three-dimensional coordinates determined by planes intersection. Our results show that the proposed method was more accurate in determining three-dimensional coordinates than plan intersection method. The obtained coordinates were evaluated and framed into the map accuracy standard for digital cartographic products (PEC-PCD), besides being analyzed for trend and precision. Accuracy analysis results frame punctual entities three-dimensional coordinates into the 1:2,000 or lower scale for Class A of PEC-PCD. Numéro de notice : A2021-959 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1590/s1982-21702021000300022 En ligne : https://doi.org/10.1590/s1982-21702021000300022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100074 [article]

Automatic filtering and 2D modeling of airborne laser scanning building point cloud / Fayez Tarsha-Kurdi in Transactions in GIS, Vol 25 n° 1 (February 2021)  

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Non-stationary extreme value analysis of ground snow loads in the French Alps: a comparison with building standards / Erwann Le Roux in Natural Hazards and Earth System Sciences, vol 20 n° 11 (November 2020)  

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Outlier detection and robust plane fitting for building roof extraction from LiDAR data / Emon Kumar Dey in International Journal of Remote Sensing IJRS, vol 41 n° 16 (01-10 May 2020)  

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Modelling of buildings from aerial LiDAR point clouds using TINs and label maps / Minglei Li in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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RoofN3D: a database for 3D building reconstruction with deep learning / Andreas Wichmann in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 6 (June 2019)  

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Piecewise horizontal 3D roof reconstruction from aerial Lidar / Slim Namouchi (2019)  

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Automatic building rooftop extraction from aerial images via hierarchical RGB-D priors / Shibiao Xu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)  

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A greyscale voxel model for airborne lidar data applied to building detection / Liying Wang in Photogrammetric record, vol 33 n° 164 (December 2018)  

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Extraction of building roof planes with stratified random sample consensus / André C. Carrilho in Photogrammetric record, vol 33 n° 163 (September 2018)  

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Three-dimensional building façade segmentation and opening area detection from point clouds / S.M. Iman Zolanvari in ISPRS Journal of photogrammetry and remote sensing, vol 143 (September 2018)  

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