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Vectorized indoor surface reconstruction from 3D point cloud with multistep 2D optimization / Jiali Han in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 177 (July 2021) . - pp 57 - 74 Titre : Vectorized indoor surface reconstruction from 3D point cloud with multistep 2D optimization Type de document : Article/Communication Auteurs : Jiali Han, Auteur ; Mengqi Rong, Auteur ; Hanqing Jiang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 57 - 74 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] champ aléatoire de Markov [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] espace intérieur [Termes descripteurs IGN] maillage [Termes descripteurs IGN] programmation linéaire [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] reconstruction d'objet [Termes descripteurs IGN] segmentation sémantique [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] vectorisation Résumé : (Auteur) Vectorized reconstruction from indoor point cloud has attracted increasing attention in recent years due to its high regularity and low memory consumption. Compared with aerial mapping of outdoor urban environments, indoor point cloud generated by LiDAR scanning or image-based 3D reconstruction usually contain more clutter and missing areas, which greatly increase the difficulty of vectorized reconstruction. In this paper, we propose an effective multistep pipeline to reconstruct vectorized models from indoor point cloud without the Manhattan or Atlanta world assumptions. The core idea behind our method is the combination of a sequence of 2D segment or cell assembly problems that are defined as global optimizations while reducing the reconstruction complexity and enhancing the robustness to different scenes. The proposed method includes a semantic segmentation stage and a reconstruction stage. First, we segment the permanent structures of indoor scenes, including ceilings, floors, walls and cylinders, from the input data, and then, we reconstruct these structures in sequence. The floorplan is first generated by detecting wall planes and selecting optimal subsets of projected wall segments with Integer Linear Programming (ILP), followed by constructing a 2D arrangement and recovering the ceiling and floor structures by Markov Random Field (MRF) labeling on the arrangement. Finally, the wall structures are modeled by lifting each edge of the arrangement to a proper height by means of another global optimization. Merging the respective results yields the final model. The experimental results show that the proposed method could obtain accurate and compact vectorized models on both precise LiDAR data and defect-laden MVS data compared with other state-of-the-art approaches. Numéro de notice : A2021-371 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.04.019 date de publication en ligne : 15/05/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.04.019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97779 [article]

Indoor mapping and modeling by parsing floor plan images / Yijie Wu in International journal of geographical information science IJGIS, vol 35 n° 6 (June 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 6 (June 2021) . - pp 1205 - 1231 Titre : Indoor mapping and modeling by parsing floor plan images Type de document : Article/Communication Auteurs : Yijie Wu, Auteur ; Jianga Shang, Auteur ; Pan Chen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1205 - 1231 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] carte d'intérieur [Termes descripteurs IGN] chevauchement [Termes descripteurs IGN] CityGML [Termes descripteurs IGN] construction [Termes descripteurs IGN] format Industry foudation classes IFC [Termes descripteurs IGN] intégrité topologique [Termes descripteurs IGN] mur [Termes descripteurs IGN] optimisation spatiale [Termes descripteurs IGN] positionnement en intérieur [Termes descripteurs IGN] vectorisation Résumé : (auteur) A large proportion of indoor spatial data is generated by parsing floor plans. However, a mature and automatic solution for generating high-quality building elements (e.g., walls and doors) and space partitions (e.g., rooms) is still lacking. In this study, we present a two-stage approach to indoor mapping and modeling (IMM) from floor plan images. The first stage vectorizes the building elements on the floor plan images and the second stage repairs the topological inconsistencies between the building elements, separates indoor spaces, and generates indoor maps and models. To reduce the shape complexity of indoor boundary elements, i.e., walls and openings, we harness the regularity of the boundary elements and extract them as rectangles in the first stage. Furthermore, to resolve the overlaps and gaps of the vectorized results, we propose an optimization model that adjusts the rectangle vertex coordinates to conform to the topological constraints. Experiments demonstrate that our approach achieves a considerable improvement in room detection without conforming to Manhattan World Assumption. Our approach also outputs instance-separate walls with consistent topology, which enables direct modeling into Industry Foundation Classes (IFC) or City Geography Markup Language (CityGML). Numéro de notice : A2021-385 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1781130 date de publication en ligne : 08/07/2020 En ligne : https://doi.org/10.1080/13658816.2020.1781130 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97642 [article]

Combining deep learning and mathematical morphology for historical map segmentation / Yizi Chen (2021)  

Public Titre : Combining deep learning and mathematical morphology for historical map segmentation Type de document : Chapitre/Contribution Auteurs : Yizi Chen, Auteur ; Edwin Carlinet, Auteur ; Joseph Chazalon, Auteur ; Clément Mallet , Auteur ; Bertrand Duménieu , Auteur ; Julien Perret , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2021 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 12708 Projets : SODUCO / Perret, Julien Conférence : DGMM 2021, 1st International Joint Conference on Discrete Geometry and Mathematical Morphology 24/05/2021 27/05/2021 Uppsala Suède Proceedings Springer Importance : pp 79 - 92 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] carte ancienne [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] données maillées [Termes descripteurs IGN] morphologie mathématique [Termes descripteurs IGN] vectorisation Résumé : (auteur) The digitization of historical maps enables the study of ancient, fragile, unique, and hardly accessible information sources. Main map features can be retrieved and tracked through the time for subsequent thematic analysis. The goal of this work is the vectorization step, i.e., the extraction of vector shapes of the objects of interest from raster images of maps. We are particularly interested in closed shape detection such as buildings, building blocks, gardens, rivers, etc. in order to monitor their temporal evolution. Historical map images present significant pattern recognition challenges. The extraction of closed shapes by using traditional Mathematical Morphology (MM) is highly challenging due to the overlapping of multiple map features and texts. Moreover, state-of-the-art Convolutional Neural Networks (CNN) are perfectly designed for content image filtering but provide no guarantee about closed shape detection. Also, the lack of textural and color information of historical maps makes it hard for CNN to detect shapes that are represented by only their boundaries. Our contribution is a pipeline that combines the strengths of CNN (efficient edge detection and filtering) and MM (guaranteed extraction of closed shapes) in order to achieve such a task. The evaluation of our approach on a public dataset shows its effectiveness for extracting the closed boundaries of objects in historical maps. Numéro de notice : H2021-001 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : 10.1007/978-3-030-76657-3_5 date de publication en ligne : 16/05/2021 En ligne : http://dx.doi.org/10.1007/978-3-030-76657-3_5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96739

Assessing historical maps for characterizing fluvial corridor changes at a regional network scale / Samuel Dunesme in Cartographica, vol 55 n° 4 (Winter 2020)  

Public [article]  inCartographica > vol 55 n° 4 (Winter 2020) . - pp 251 - 265 Titre : Assessing historical maps for characterizing fluvial corridor changes at a regional network scale Type de document : Article/Communication Auteurs : Samuel Dunesme , Auteur ; Hervé Piegay, Auteur ; Sébastien Mustière , Auteur Année de publication : 2020 Projets : EUR H20'Lyon / Article en page(s) : pp 251 - 265 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] base de données historiques [Termes descripteurs IGN] base de données topographiques [Termes descripteurs IGN] carte de base [Termes descripteurs IGN] corridor biologique [Termes descripteurs IGN] données hydrographiques [Termes descripteurs IGN] géomorphologie [Termes descripteurs IGN] rivière [Termes descripteurs IGN] trame bleue [Termes descripteurs IGN] vectorisation [Termes descripteurs IGN] vingtième siècle Résumé : (Auteur) Fluvial corridor quality assessment requires that historical data be collected at a regional scale. In this article, our goal is to assess potential map resources to explore riverscape changes at a regional network scale and to define key issues in using an automated vectorization protocol to characterize such changes on such a large scale. We consider IGN’s Nouvelle Carte de France a potentially good resource for our objective of two-date (oldest + actual vector database) comparisons on 1:20,000–1:25,000 scale maps, notably when applied at a regional scale. The French IGN corpus is a good example of topographic maps that were produced in the twentieth century in Europe with fairly homogeneous data over a whole national territory. Moreover, the digitization and georeferencing processes applied by IGN are very accurate. The evolution of conventional features is not as significant for the hydrographic theme and should not be a problem for automatic vectorization. The potential temporal coverage is from 1922 to 1993, but the complexity of the sheet divisions, partial revisions, and the heterogeneity of coverage over time prevent multidate analysis. Numéro de notice : A2020-775 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2019-0025 date de publication en ligne : 22/12/2020 En ligne : https://doi.org/10.3138/cart-2019-0025 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96689 [article]

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Can we characterize river corridor evolution at a continental scale from historical topographic maps? A first assessment from the comparison of four countries / J. Horacio Garcia in River Research and Applications, vol 36 n° 6 (July 2020)  

Public [article]  inRiver Research and Applications > vol 36 n° 6 (July 2020) . - pp 934 - 946 Titre : Can we characterize river corridor evolution at a continental scale from historical topographic maps? A first assessment from the comparison of four countries Type de document : Article/Communication Auteurs : J. Horacio Garcia, Auteur ; Samuel Dunesme , Auteur ; Hervé Piegay, Auteur Année de publication : 2020 Projets : EUR H20'Lyon / Article en page(s) : pp 934 - 946 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] Belgique [Termes descripteurs IGN] carte ancienne [Termes descripteurs IGN] corridor biologique [Termes descripteurs IGN] dix-neuvième siècle [Termes descripteurs IGN] forêt ripicole [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] rivière [Termes descripteurs IGN] Suisse [Termes descripteurs IGN] vectorisation Résumé : (auteur) National historical map resources are assessed in four European countries to characterize river corridor features and associated channel changes, as well as identify issues limiting or promoting geomorphic assessment procedures at a continental scale. A geomorphic audit that launches potential data for diagnosis from reach to continental scales could offer a good resource for biology and ecology managers of river authorities or government agencies and engineers. The assessment compares the resources available by country in terms of period covered, spatial scale, history and chronology, and representation of the fluvial corridor features. We then applied the Historical Maps Vectorization Toolbox, initially developed for vectorizing river corridors from French maps, to detect and extract flow channels, unvegetated bars and riparian vegetation patches from historical topographical maps. We found that (a) it is difficult to apply an audit of channel changes to the whole continental scale because map legends differ between countries due to geographic and political specificity; (b) there exists an opportunity to get assessment information in all countries at reach or national scale where map resources are available; (c) the highest potential is observed in Switzerland and Belgium where there is high quality national map coverage from the 19th century; and (d) the algorithm Historical Maps Vectorization Toolbox applied to map resources works well with any of the countries, and its widespread application is encouraging. Numéro de notice : A2020-362 Affiliation des auteurs : ENSG+Ext (2012-2019) Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1002/rra.3582 date de publication en ligne : 30/12/2019 En ligne : https://doi.org/10.1002/rra.3582 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95333 [article]

A discriminative tensor representation model for feature extraction and classification of multispectral LiDAR data / Qingwang Wang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Détection et vectorisation automatiqued’objets linéaires dans des nuages de points de voirie / Etienne Barçon (2020)  

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Des images satellites aux cartes vectorielles / Onur Tasar (2020)  

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Learning and geometric approaches for automatic extraction of objects from remote sensing images / Nicolas Girard (2020)  

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Very high resolution land cover mapping of urban areas at global scale with convolutional neural network / Thomas Tilak (2020)  

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Des empreintes cartographiques : restitution de données géohistoriques à partir de la Carte de France de Cassini, 1750-1789 / Bertrand Duménieu in Cartes & Géomatique, n° 241-242 (décembre 2019)

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Une nouvelle méthode de vectorisation du cadastre ancien / Antony Chalais in Géomatique expert, n° 129 (août - septembre 2019)

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An image-pyramid-based raster-to-vector conversion (IPBRTVC) framework for consecutive-scale cartography and synchronized generalization of classic objects / Chang Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)  

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Lever-nivelé de la place de Barcelone, 1823-1827 / Blanca Baella in Cartes & Géomatique, n° 238 (Décembre 2018)

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Une méthodologie nationale pour le géoréférencement et la vectorisation des cartes d’état-major, minutes au 1/40 000 / Thierry Lallemant in Revue forestière française [en ligne], vol 69 n° 4-5 (2017)  

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