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Photogrammetric 3D mobile mapping of rail tracks / Philipp Glira in ISPRS Journal of photogrammetry and remote sensing, vol 183 (January 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 183 (January 2022) . - pp 352 - 362 Titre : Photogrammetric 3D mobile mapping of rail tracks Type de document : Article/Communication Auteurs : Philipp Glira, Auteur ; K. ÖlsböckK., Auteur ; T. Kadiofsky, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 352 - 362 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Autriche [Termes IGN] axe médian [Termes IGN] compensation par faisceaux [Termes IGN] compensation par moindres carrés [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] modèle numérique de surface [Termes IGN] OpenStreetMap [Termes IGN] orthoimage [Termes IGN] point d'appui [Termes IGN] reconstruction 3D [Termes IGN] réseau ferroviaire [Termes IGN] semis de points [Termes IGN] voie ferrée Résumé : (auteur) Recent developments in the field of rail vehicles increased the demand for accurate and up-to-date 3D maps of rail track networks. Collision avoidance systems, semi-automated, or fully autonomous rail vehicles strongly benefit from such high quality maps. In this work, we present a fully automatic, photogrammetric method for the 3D reconstruction of rail track segments. More specifically, the center line of the rail track is reconstructed as a georeferenced and continuous 3D cubic spline. The main data inputs are collected while driving the rail vehicle along the segment: (a) images from a front-looking camera and (b) observations from a low-cost GNSS receiver. Optional data inputs can be used to increase the reconstruction accuracy, namely (c) an a priori rail track (e.g. from OpenStreetMap), (d) a digital height model (DHM), and (e) ground control points (GCPs). The rail track is estimated in post processing (offline) by a weighted least squares adjustment (LSA). The core of the LSA is the bundle adjustment of images. It is extended by additional geometric constraints which exploit the geometric relations between the rail track, the rail vehicle, and the camera trajectory. As a consequence, in contrast to many related methods, the rails need not to be visible in the images to map the rail track. We applied the method to reconstruct a 13 km long tram line in Vienna (Austria). We found that the local geometry of the track can be well reconstructed from the image sequence. However, if the low-cost GNSS receiver is used as single georeferencing source, the track shows a strong drift behavior. This drift can significantly be minimized over the entire track if the above mentioned optional data inputs are used. Numéro de notice : A2022-034 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2021.09.006 Date de publication en ligne : 01/12/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.09.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99327 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2022011	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2022013	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2022012	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

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)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 5 n° 1 (June 2021) . - n° 10 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 points Résumé : (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 [article]

Automatic object extraction from airborne laser scanning point clouds for digital base map production / Elyta Widyaningrum (2021)  

Public Titre : Automatic object extraction from airborne laser scanning point clouds for digital base map production Type de document : Thèse/HDR Auteurs : Elyta Widyaningrum, Auteur Editeur : Delft [Pays-Bas] : Delft University of Technology Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] axe médian [Termes IGN] chaîne de traitement [Termes IGN] détection d'objet [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction du réseau routier [Termes IGN] image aérienne [Termes IGN] orthoimage [Termes IGN] semis de points [Termes IGN] squelettisation [Termes IGN] transformation de Hough [Termes IGN] vectorisation Résumé : (auteur) A base map provides essential geospatial information for applications such as urban planning, intelligent transportation systems, and disaster management. Buildings and roads are the main ingredients of a base map and are represented by polygons. Unfortunately, manually delineating their boundaries from remote sensing data is time consuming and labour intensive. Airborne laser scanning (ALS) point clouds provide dense and accurate 3D positional information. Automatic extraction of buildings and roads from 3D point clouds is challenging because of their irregular shapes, occlusions in the data, and irregularity of ALS point clouds. This study focuses on two particular objectives: (i) accurate classification of a large volume of ALS 3D point clouds; and (ii) smooth and accurate building and road outline extraction. To achieve the classification objective, we perform point-wise deep learning to classify an ALS point cloud of a complex urban scene in Surabaya, Indonesia. The point cloud is colored by airborne orthophotos. Training data is obtained from an existing 2D topographic base map by a semi-automatic method proposed in this research. A dynamic-graph convolutional neural network is used to classify the point cloud into four classes: bare land, trees, buildings, and roads. We investigate effective input feature combinations for outdoor point cloud classification. A highly acceptable classification result of 91.8% overall accuracy is achieved when using the full combination of RGB color and LiDAR features. To address the objective of outline extraction, we propose building and road outline extraction methods that run directly on ALS point cloud data. For accurate and smooth building outline extraction, we propose two different methods. First, we develop the ordered Hough transform (OHT), which is an extension of the traditional Hough transform, by explicitly incorporating the sequence of points to form the outline. Second, we propose a new method based on Medial Axis Transform (MAT) skeletons which takes advantage of the skeleton points to detect building corners. The OHT method is resistant to noise but it requires prior knowledge on a building’s main directions. On the contrary, the MAT-based method does not require such orientation initialization but is more sensitive to noise on building edges. We compare the results of our building outline extraction methods to an existing RANSAC-based method, in terms of geometric accuracy, completeness of building corners, and computation time, and demonstrate that the MAT-based approach has the highest geometric accuracy, results in more complete building corners, and is slightly faster than other methods. For road network extraction, we develop a method based on skeletonization, which results in complete and continuous road centerlines and boundaries. In our study area, several roads are disrupted and disconnected due to trees. We design a tree-constrained approach to fill road gaps and integrate road width estimated from a medial axis algorithm. Comparison to reference data shows that the proposed method is able to extract almost all existing roads in the study area, and even detects roads that were not present in the reference due to human errors. We conclude that our object extraction methods enable a complete automatic procedure, extracting more accurate building and road outlines from ALS point cloud data. This contributes to a higher automation readiness level for a faster and cheaper base map production. Numéro de notice : 17664 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Thèse étrangère Note de thèse : PhD thesis : Sciences : TU Delft: 2021 Date de publication en ligne : 10/03/2021 En ligne : https://doi.org/10.4233/uuid:8900fac8-a76c-482a-b280-e1758783b5b3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97984

Semi-automated framework for generating cycling lane centerlines on roads with roadside barriers from noisy MLS data / Yang Ma in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 167 (September 2020) . - pp 396 - 417 Titre : Semi-automated framework for generating cycling lane centerlines on roads with roadside barriers from noisy MLS data Type de document : Article/Communication Auteurs : Yang Ma, Auteur ; Yubing Zheng, Auteur ; Said Easa, Auteur ; Jianchuan Cheng, Auteur Année de publication : 2020 Article en page(s) : pp 396 - 417 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] axe médian [Termes IGN] bicyclette [Termes IGN] classification par nuées dynamiques [Termes IGN] classification semi-dirigée [Termes IGN] numérisation automatique [Termes IGN] rastérisation [Termes IGN] sécurité routière [Termes IGN] segmentation [Termes IGN] télémétrie laser mobile [Termes IGN] tracé routier Résumé : (auteur) Cycling lane centerlines (CLC) play an important role in the evaluation of safety-related conditions and guiding systems for cyclists along road corridors. The unavailability of design files or undocumented changes in the road infrastructures after improvements has created great difficulty in delineating CLC on existing roads. In this study, mobile laser scanning (MLS) data are introduced into this domain and a four-step semi-automated framework is proposed for generating CLC on roads with roadside barriers (RB). First, MLS data are restructured into the aligned scan-pattern grid using the mapping trajectory data. Second, a rasterization-based clustering approach is applied to segment the off-ground objects from the reorganized MLS data. Third, the RB amongst the segmented objects are identified using a sequential application of the k-Means clustering method and the proposed unidirectional growing method. Finally, the moving average technique and natural cubic spline are applied to generate CLC from the critical positions alongside the identified RB. Testing on three road sections with different types of RB demonstrated that the developed framework can successfully generate CLC from MLS data in the presence of considerable noises. The results also show that the proposed procedure shows better accuracy performance on processing roads with wide RB than a road with narrow RB. Numéro de notice : A2020-550 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.07.009 Date de publication en ligne : 04/08/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.07.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95779 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020091	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2020093	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2020092	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

An indoor navigation model and its network extraction / Filippo Mortari in Applied geomatics, Vol 11 n° 4 (December 2019)  

Public [article]  inApplied geomatics > Vol 11 n° 4 (December 2019) . - pp 413–427 Titre : An indoor navigation model and its network extraction Type de document : Article/Communication Auteurs : Filippo Mortari, Auteur ; Eliseo Clementini, Auteur ; Sisi Zlatanova, Auteur ; Liu Liu, Auteur Année de publication : 2019 Article en page(s) : pp 413–427 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] axe médian [Termes IGN] CityGML [Termes IGN] diagramme de Voronoï [Termes IGN] espace topologique [Termes IGN] extraction automatique [Termes IGN] extraction de données [Termes IGN] modèle géométrique du bâti [Termes IGN] modèle numérique du bâti [Termes IGN] modélisation 3D [Termes IGN] positionnement en intérieur [Termes IGN] raisonnement spatiotemporel [Termes IGN] représentation spatio-sémantique Résumé : (auteur) We propose a navigation model for indoor environments that combines a 3D geometric modeling of buildings with connection properties of spaces and semantic elements such as openings and installations. The model is an extension of the IndoorGML standard navigation module with a twofold benefit: the extension facilitated the data import from the international standard CityGML and introduced the semantics of various fixtures in indoor space of buildings making the navigation model more suitable for human needs. Several experiments have been conducted by extracting networks from CityGML data and performing a comparison with other network construction techniques. The second contribution of the paper is an algorithm for the automatic extraction of the navigation network. Such an algorithm is a hybrid solution between medial axis approaches and visibility graph approaches. Normally, medial axes approaches are a good representation of human navigation in narrow corridors, especially to avoid obstacles, but introduce distortions in open space. On the other hand, visibility approaches work better in open spaces. In our extraction technique, the resulting network takes advantages of both approaches and better mimics human beings’ navigation in indoor environments. Numéro de notice : A2019-534 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-019-00273-8 Date de publication en ligne : 17/06/2019 En ligne : https://doi.org/10.1007/s12518-019-00273-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94129 [article]

Analysing the positional accuracy of GNSS multi-tracks obtained from VGI sources to generate improved 3D mean axes / Antonio Tomás Mozas-Calvache in International journal of geographical information science IJGIS, vol 33 n° 11 (November 2019)  

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Large scale semi-automatic detection of forest roads from low density LiDAR data on steep terrain in Northern Spain / Convadonga Prendes in iForest, biogeosciences and forestry, vol 12 n° 4 (July 2019)  

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Simultaneous chain-forming and generalization of road networks / Susanne Wenzel in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)  

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Labelling hierarchy for street maps using centrality measures / Wasim Shoman in Cartographic journal (the), vol 55 n° 1 (February 2018)  

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Centrality-based hierarchy for street network generalization in multi-resolution maps / Wasim Shoman in Geocarto international, vol 32 n° 12 (December 2017)  

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An iterative method for obtaining a mean 3D axis from a set of GNSS traces for use in positional controls / A. Mozas-Calvache in Survey review, vol 49 n° 355 (October 2017)  

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A simplified linear feature matching method using decision tree analysis, weighted linear directional mean, and topological relationships / Ick-Hoi Kim in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

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Using vector building maps to aid in generating seams for low-attitude aerial orthoimage mosaicking: Advantages in avoiding the crossing of buildings / Dongliang Wang in ISPRS Journal of photogrammetry and remote sensing, vol 125 (March 2017)  

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Robust approximation of the Medial Axis Transform of LiDAR point clouds as a tool for visualisation / Ravi Peters in Computers & geosciences, vol 90 part A (May 2016)  

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Cartographie routière navigable sur Tahiti : Référentiel routier / Anna Mouget (2014)

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