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3D reconstruction of bridges from airborne laser scanning data and cadastral footprints / Steffen Goebbels in Journal of Geovisualization and Spatial Analysis, vol 5 n° 1 (June 2021)
[article]
Titre : 3D reconstruction of bridges from airborne laser scanning data and cadastral footprints Type de document : Article/Communication Auteurs : Steffen Goebbels, Auteur Année de publication : 2021 Article en page(s) : n° 10 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Allemagne
[Termes IGN] axe médian
[Termes IGN] CityGML
[Termes IGN] données cadastrales
[Termes IGN] données lidar
[Termes IGN] empreinte
[Termes IGN] pont
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction 3D
[Termes IGN] semis de pointsRésumé : (auteur) The given paper describes a method for automatic 3D reconstruction of bridges from cadastral footprints and airborne laser scanning point clouds. The reconstructed bridges are used to enrich 3D city models. Unlike roofs, decks of bridges are typically smooth without ridge lines or step edges. Therefore, established methods for roof reconstruction are not suitable for bridges. The standard description language for semantic city models is CityGML. This specification of the Open Geospatial Consortium assumes that surfaces are composed of planar polygons. The approximation of smooth decks by planar polygons is achieved by using a medial axis tree. Instead of the medial axis of the footprint, a modified medial axis is computed that does not consider counter bearing edges. The resulting tree represents centerline connections between all counter bearing edges and, in conjunction with filtered height values of a point cloud, serves as the basis for approximation with polygons. In addition to modeling decks, superstructures such as pylons and cables are also derived from the point cloud. For this purpose, planes carrying many superstructure points are detected using the Random Sampling Consensus Algorithm (RANSAC). Images are generated by projecting points onto these planes. Then, image processing methods are used to find connected contours that are extruded to form 3D objects. The presented method was successfully applied to all bridges of two German cities as well as to large bridges built over the Rhine River. Numéro de notice : A2021-359 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s41651-021-00076-9 Date de publication en ligne : 12/04/2021 En ligne : https://doi.org/10.1007/s41651-021-00076-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97623
in Journal of Geovisualization and Spatial Analysis > vol 5 n° 1 (June 2021) . - n° 10[article]Automated calibration of smartphone cameras for 3D reconstruction of mechanical pipes / Reza Maalek in Photogrammetric record, vol 36 n° 174 (June 2021)
[article]
Titre : Automated calibration of smartphone cameras for 3D reconstruction of mechanical pipes Type de document : Article/Communication Auteurs : Reza Maalek, Auteur ; Derek D. Lichti, Auteur Année de publication : 2021 Article en page(s) : pp 124 - 146 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] appariement de formes
[Termes IGN] auto-étalonnage
[Termes IGN] canalisation
[Termes IGN] compensation par faisceaux
[Termes IGN] ellipse
[Termes IGN] étalonnage d'instrument
[Termes IGN] reconstruction 3D
[Termes IGN] structure-from-motion
[Termes IGN] téléphone intelligent
[Termes IGN] triangulationRésumé : (auteur) This paper outlines a new framework for the calibration of optical instruments, in particular smartphone cameras, using highly redundant circular black-and-white target fields. New methods were introduced for (i) matching targets between images; (ii) adjusting the systematic eccentricity error of target centres; and (iii) iteratively improving the calibration solution through a free-network self-calibrating bundle adjustment. The proposed method effectively matched circular targets in 270 smartphone images, taken within a calibration laboratory, with robustness to type II errors (false negatives). The proposed eccentricity adjustment, which requires only camera projective matrices from two views, behaved comparably to available closed-form solutions, which require additional a priori object-space target information. Finally, specifically for the case of mobile devices, the calibration parameters obtained using the framework were found to be superior compared to in situ calibration for estimating the 3D reconstructed radius of a mechanical pipe (approximately 45% improvement on average). Numéro de notice : A2021-512 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12364 Date de publication en ligne : 06/06/2021 En ligne : https://doi.org/10.1111/phor.12364 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97929
in Photogrammetric record > vol 36 n° 174 (June 2021) . - pp 124 - 146[article]Predicting tree species based on the geometry and density of aerial laser scanning point cloud of treetops / Nina Kranjec in Geodetski vestnik, vol 65 n° 2 (June - August 2021)
[article]
Titre : Predicting tree species based on the geometry and density of aerial laser scanning point cloud of treetops Type de document : Article/Communication Auteurs : Nina Kranjec, Auteur ; Mihaela Triglav Cekada, Auteur ; Milan Kobal, Auteur Année de publication : 2021 Article en page(s) : pp 234 - 259 Note générale : bibliographie Langues : Anglais (eng) Slovène (slv) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Acer pseudoplatanus
[Termes IGN] apprentissage automatique
[Termes IGN] arbre de décision
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] Fagus sylvatica
[Termes IGN] feuillu
[Termes IGN] figure géométrique
[Termes IGN] Fraxinus excelsior
[Termes IGN] houppier
[Termes IGN] identification automatique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Larix decidua
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Picea abies
[Termes IGN] Pinophyta
[Termes IGN] Pinus sylvestris
[Termes IGN] semis de points
[Termes IGN] SlovénieRésumé : (auteur) Based on the laser point clouds of 240 individual trees that were also identified in the field, we developed decision trees to distinguish deciduous and coniferous trees and individual tree species: Picea abies, Larix decidua, Pinus sylvestris, Fagus sylvatica, Acer pseudoplatanus, Fraxinus excelsior. The volume of the upper part of the tree crown (height of 3 m) and the average intensity of the laser reflections were used as explanatory variables. There were four aerial laser datasets: May 2012, September 2012, March 2013 and July 2015. We found that the combination of the volume and the average intensity of the first three laser datasets was the most reliable for predicting the selected tree species (60% model performance). A slightly poorer model performance was obtained if only the average intensity of the first three datasets was used (54% model performance). The worst model performance was given by the intensities (31 % model performance) or the volumes (21 % model performance) of dataset 4, which represents the national laser scanning of Slovenia (LSS). The best performing was the deciduous and coniferous separation, which achieved 75% and 95% success based on the test data (combination of volume and average intensity of the first three laser datasets). Using only the LSS intensities, deciduous and coniferous trees could be separated with 81% success. Numéro de notice : A2021-559 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.15292/geodetski-vestnik.2021.02.234-259 Date de publication en ligne : 27/05/2021 En ligne : https://doi.org/10.15292/geodetski-vestnik.2021.02.234-259 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98113
in Geodetski vestnik > vol 65 n° 2 (June - August 2021) . - pp 234 - 259[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 139-2021021 RAB Revue Centre de documentation En réserve L003 Disponible Robust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds / Reza Maalek in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)
[article]
Titre : Robust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds Type de document : Article/Communication Auteurs : Reza Maalek, Auteur ; Derek Litchi, Auteur Année de publication : 2021 Article en page(s) : pp 83 - 108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] chevauchement
[Termes IGN] cylindre
[Termes IGN] détection de cible
[Termes IGN] données localisées 3D
[Termes IGN] ellipticité (géométrie)
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image 2D
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] méthode robuste
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de pointsRésumé : (auteur) Detection of non-overlapping ellipses from 2-dimensional (2D) edge points is an essential step towards solving typical photogrammetry problems pertaining to feature detection, calibration, and registration of optical instruments. For instance, circular and spherical black and white calibration and registration targets are represented as ellipses in images. Furthermore, the intersection of a cut plane with cylindrical point clouds generates 2D points following elliptic patterns. To this end, this study proposes a collection of new methods for the automatic and robust detection of non-overlapping ellipses from 2D points. These methods will first be applied to detect circular and spherical targets in images and, second, to detect cylinders in 3D point clouds. The method utilizes the Euclidian ellipticity and a new systematic and generalizable threshold to decide if a set of connected points follow an elliptic pattern. When connected points include outliers, the newly proposed robust Monte Carlo-based ellipse fitting method will be deployed. This method includes three new developments: (i) selecting initial subsamples using a bucketing strategy based on the polar angle of the points; (ii) detecting inlier points by reducing the robust ellipse fitting to a robust circle fitting problem; and (iii) choosing the best inlier set amongst all subsamples using adaptive, systematic, and generalizable selection criteria. A new process is presented to extract cylinders from a point cloud by detecting non-overlapping ellipses from the points projected onto an intersecting cut plane. The proposed methods were compared to established state-of-the-art methods, using simulated and real-world datasets, through the design of four sets of original experiments. The experiments include (i) comparisons of robust ellipse fitting; (ii) sensitivity analysis of the ellipse validation criteria; (iii) comparison of non-overlapping ellipse detection; and (iv) detection of pipes from terrestrial laser scanner point clouds. It was found that the proposed robust ellipse detection was superior to four reliable robust methods, including the popular least median of squares, in both simulated and real-world datasets. The proposed process for detecting non-overlapping ellipses achieved F-measure of 99.3% on real images, compared to 42.4%, 65.6%, and 59.2%, obtained using the methods of Fornaciari, Patraucean, and Panagiotakis, respectively. The proposed cylinder extraction method identified all detectable mechanical pipes in two real-world point clouds collected in laboratory and industrial construction site conditions. The results of this investigation show promise for the application of the proposed methods for automatic extraction of circular targets from images and pipes from point clouds. Numéro de notice : A2021-413 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2021.04.010 Date de publication en ligne : 28/04/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.04.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97744
in ISPRS Journal of photogrammetry and remote sensing > vol 176 (June 2021) . - pp 83 - 108[article]An integrated method for DEM simplification with terrain structural features and smooth morphology preserved / Wenhao Yu in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)
[article]
Titre : An integrated method for DEM simplification with terrain structural features and smooth morphology preserved Type de document : Article/Communication Auteurs : Wenhao Yu, Auteur ; Yifan Zhang, Auteur ; Tinghua Ai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 273 - 295 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse structurelle
[Termes IGN] arête
[Termes IGN] carte géomorphologique
[Termes IGN] filtrage statistique
[Termes IGN] ligne caractéristique
[Termes IGN] limite de terrain
[Termes IGN] modèle numérique de surface
[Termes IGN] visualisation multiéchelleRésumé : (auteur) As a key focus of cartography and terrain analysis, the simplification of a digital elevation model (DEM) is used to preserve the pattern features of the terrain surface while suppressing its details over multiple scales. Statistical filtering and structural analysis methods are commonly used for this process. The structural analysis method performs well in identifying terrain structural edges, while it tends to discard the smooth morphology of a terrain surface. In addition, the filter that aims to reduce noise on a surface may over-smooth the terrain structural edges. Therefore, to preserve both the terrain structural edges and smooth morphology, we propose to combine the techniques of statistical filtering and structural analysis. Specifically, all the critical elevation points and structural edges are first detected from the DEM surface by using the structural analysis method. Then, the iterative guided normal filter is used to smooth the generalized DEM with the guidance of the structure of the original surface. After this process, the terrain structure is retained in the smooth surface of the DEM. The experimental results with a real-world dataset show that our method can inherit the merits of both structural analysis and statistical filter in preserving terrain features for multi-scale DEM representations. Numéro de notice : A2021-038 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1772479 Date de publication en ligne : 29/05/2020 En ligne : https://doi.org/10.1080/13658816.2020.1772479 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96747
in International journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 273 - 295[article]Curved buildings reconstruction from airborne LiDAR data by matching and deforming geometric primitives / Jingwei Song in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)PermalinkAutomatic object extraction from airborne laser scanning point clouds for digital base map production / Elyta Widyaningrum (2021)PermalinkLearning-based representations and methods for 3D shape analysis, manipulation and reconstruction / Marie-Julie Rakotosaona (2021)PermalinkLearning embeddings for cross-time geographic areas represented as graphs / Margarita Khokhlova (2021)PermalinkPanoptic segmentation of satellite image time series with convolutional temporal attention networks / Vivien Sainte Fare Garnot (2021)PermalinkSupplementary material for: Panoptic segmentation of satellite image time series with convolutional temporal attention networks / Vivien Sainte Fare Garnot (2021)PermalinkPermalinkParsing very high resolution urban scene images by learning deep ConvNets with edge-aware loss / Xianwei Zheng in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)PermalinkA multi-scale representation model of polyline based on head/tail breaks / Pengcheng Liu in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)PermalinkChoosing an appropriate training set size when using existing data to train neural networks for land cover segmentation / Huan Ning in Annals of GIS, vol 26 n° 4 (October 2020)Permalink