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3D building model simplification method considering both model mesh and building structure / Jiangfeng She in Transactions in GIS, vol 26 n° 3 (May 2022)
[article]
Titre : 3D building model simplification method considering both model mesh and building structure Type de document : Article/Communication Auteurs : Jiangfeng She, Auteur ; Bo Chen, Auteur ; Junzhong Tan, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1182 - 1203 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] contour
[Termes IGN] contrainte géométrique
[Termes IGN] empreinte
[Termes IGN] maillage
[Termes IGN] maillage par triangles
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] saillance
[Termes IGN] simplification de maillage
[Termes IGN] simplification de surfaceRésumé : (auteur) The simplification of three-dimensional (3D) building models to improve rendering efficiency has gained widespread attention. To maintain the model's overall appearance features while increasing the simplification rate, we propose a novel 3D building simplification method that considers both the model mesh and building structure. The method divides a 3D building into a primary structure and subsidiary structures. It then organizes these structures using StructureTree, a multi-way tree. The structures are organized according to the dependency relationships between building structures. When simplifying a building, the decision whether to simplify the mesh or remove the subsidiary structure in the leaf node of the StructureTree depends on the volume change caused by the edge collapse and the visual saliency of the removed structure. The experimental results show that our method exhibits a better simplification effect than the traditional simplification method, and the proposed method can achieve a high simplification rate while maintaining the simplification quality. Furthermore, the results of some spatial analyses based on the highly simplified building model are consistent with those of the original model. Numéro de notice : A2022-464 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : https://doi.org/10.1111/tgis.12907 Date de publication en ligne : 14/02/2022 En ligne : https://doi.org/10.1111/tgis.12907 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100792
in Transactions in GIS > vol 26 n° 3 (May 2022) . - pp 1182 - 1203[article]GeoRec: Geometry-enhanced semantic 3D reconstruction of RGB-D indoor scenes / Linxi Huan in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)
[article]
Titre : GeoRec: Geometry-enhanced semantic 3D reconstruction of RGB-D indoor scenes Type de document : Article/Communication Auteurs : Linxi Huan, Auteur ; Xianwei Zheng, Auteur ; Jianya Gong, Auteur Année de publication : 2022 Article en page(s) : pp 301 - 314 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] données localisées 3D
[Termes IGN] géométrie
[Termes IGN] image RVB
[Termes IGN] maillage
[Termes IGN] modélisation sémantique
[Termes IGN] objet 3D
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] scène intérieureRésumé : (auteur) Semantic indoor 3D modeling with multi-task deep neural networks is an efficient and low-cost way for reconstructing an indoor scene with geometrically complete room structure and semantic 3D individuals. Challenged by the complexity and clutter of indoor scenarios, the semantic reconstruction quality of current methods is still limited by the insufficient exploration and learning of 3D geometry information. To this end, this paper proposes an end-to-end multi-task neural network for geometry-enhanced semantic 3D reconstruction of RGB-D indoor scenes (termed as GeoRec). In the proposed GeoRec, we build a geometry extractor that can effectively learn geometry-enhanced feature representation from depth data, to improve the estimation accuracy of layout, camera pose and 3D object bounding boxes. We also introduce a novel object mesh generator that strengthens the reconstruction robustness of GeoRec to indoor occlusion with geometry-enhanced implicit shape embedding. With the parsed scene semantics and geometries, the proposed GeoRec reconstructs an indoor scene by placing reconstructed object mesh models with 3D object detection results in the estimated layout cuboid. Extensive experiments conducted on two benchmark datasets show that the proposed GeoRec yields outstanding performance with mean chamfer distance error for object reconstruction on the challenging Pix3D dataset, 70.45% mAP for 3D object detection and 77.1% 3D mIoU for layout estimation on the commonly-used SUN RGB-D dataset. Especially, the mesh reconstruction sub-network of GeoRec trained on Pix3D can be directly transferred to SUN RGB-D without any fine-tuning, manifesting a high generalization ability. Numéro de notice : A2022-235 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2022.02.014 Date de publication en ligne : 03/03/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.02.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100139
in ISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 301 - 314[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2022041 SL Revue Centre de documentation Revues en salle Disponible 081-2022043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2022042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt A cost-effective method for reconstructing city-building 3D models from sparse Lidar point clouds / Marek Kulawiak in Remote sensing, vol 14 n° 5 (March-1 2022)
[article]
Titre : A cost-effective method for reconstructing city-building 3D models from sparse Lidar point clouds Type de document : Article/Communication Auteurs : Marek Kulawiak, Auteur Année de publication : 2022 Article en page(s) : n° 1278 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Bâti-3D
[Termes IGN] contour
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Gdansk
[Termes IGN] maillage
[Termes IGN] modélisation 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points clairsemés
[Termes IGN] triangulation de DelaunayRésumé : (auteur) The recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital representations of cities; however, reconstructing 3D building shapes from a sparse point cloud is a time-consuming process because automatic shape reconstruction methods work best with dense point clouds and usually cannot be applied for this purpose. Moreover, existing methods dedicated to reconstructing simplified 3D buildings from sparse point clouds are optimized for detecting simple building shapes, and they exhibit problems when dealing with more complex structures such as towers, spires, and large ornamental features, which are commonly found e.g., in buildings from the renaissance era. In the above context, this paper proposes a novel method of reconstructing 3D building shapes from sparse point clouds. The proposed algorithm has been optimized to work with incomplete point cloud data in order to provide a cost-effective way of generating representative 3D city models. The algorithm has been tested on lidar point clouds representing buildings in the city of Gdansk, Poland. Numéro de notice : A2022-211 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14051278 Date de publication en ligne : 05/03/2022 En ligne : https://doi.org/10.3390/rs14051278 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100044
in Remote sensing > vol 14 n° 5 (March-1 2022) . - n° 1278[article]Exploiting light directionality for image-based 3D reconstruction of non-collaborative surfaces / Ali Karami in Photogrammetric record, vol 37 n° 177 (March 2022)
[article]
Titre : Exploiting light directionality for image-based 3D reconstruction of non-collaborative surfaces Type de document : Article/Communication Auteurs : Ali Karami, Auteur ; Fabio Menna, Auteur ; Fabio Remondino, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 111 - 138 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement d'images
[Termes IGN] axe de prise de vue
[Termes IGN] étalonnage
[Termes IGN] figure géométrique
[Termes IGN] point d'appui
[Termes IGN] points homologues
[Termes IGN] rayonnement lumineux
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de pointsRésumé : (auteur) Three-dimensional (3D) measurement of non-collaborative surfaces is still an open research topic. This paper investigates and quantifies for the first time the effect of light directionality and fusion of multiple images as a method to improve the quality of photogrammetric 3D reconstruction. For this aim, an image acquisition system that employs multiple light sources was developed to highlight the roughness and microstructures of the object under investigation. Images were captured at various grazing angles to highlight the local surface roughness and microstructures. Individual point clouds, created using images taken at different grazing angles, were produced using dense image-matching techniques. These point clouds were then compared against different 3D photogrammetric reconstructions obtained from a pre-processing of the acquired images based on diffuse lighting, median and average images. Experiments showed that exploiting light directionality significantly improves image-matching quality. Furthermore, depending on the light direction, the root mean square (RMS) error of the 3D surfaces obtained using the proposed system were up to 50% less than those created by traditional diffuse lighting. Numéro de notice : A2022-208 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12400 Date de publication en ligne : 07/03/2022 En ligne : https://doi.org/10.1111/phor.12400 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100218
in Photogrammetric record > vol 37 n° 177 (March 2022) . - pp 111 - 138[article]
Titre : A 3D segments based algorithm for heterogeneous data registration Type de document : Article/Communication Auteurs : Rahima Djahel, Auteur ; Pascal Monasse, Auteur ; Bruno Vallet , Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2022 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B1 Projets : 1-Pas de projet / Conférence : ISPRS 2022, Commission 1, 24th ISPRS international congress, Imaging today, foreseeing tomorrow 06/06/2022 11/06/2022 Nice France OA ISPRS Archives Importance : pp 129 - 136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme du recuit simulé
[Termes IGN] données hétérogènes
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] orthoimage
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction 3D
[Termes IGN] segment de droite
[Termes IGN] superposition de donnéesRésumé : (auteur) Combining image and LiDAR draws increasing interest in surface reconstruction, city and building modeling for constructing 3D virtual reality models because of their complementary nature. However, to gain from this complementarity, these data sources must be precisely registered. In this paper, we propose a new primitive based registration algorithm that takes 3D segments as features. The objective of the proposed algorithm is to register heterogeneous data. The heterogeneity is both in data type (image and LiDAR) and acquisition platform (terrestrial and aerial). Our algorithm starts by extracting 3D segments from LiDAR and image data with state of the art algorithms. Then it clusters the 3D segments of each data according to their directions. The obtained clusters are associated to find possible rotations, then 3D segments from associated clusters are matched in order to find the translation and scale factor minimizing a distance criteria between the two sets of 3D segments. Two optimizers (simulated annealing and RANSAC) are tested to minimize this distance criterion, first on synthetic data, then on real data. The experiments carried out demonstrate the robustness and speed of RANSAC compared to simulated annealing. Numéro de notice : C2022-018 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B1-2022-129-2022 Date de publication en ligne : 30/05/2022 En ligne : http://dx.doi.org/10.5194/isprs-archives-XLIII-B1-2022-129-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100844 PermalinkPermalinkPermalinkPermalinkGéophysique / Jacques Dubois (2022)PermalinkPermalinkPermalinkPhotogrammetric 3D mobile mapping of rail tracks / Philipp Glira in ISPRS Journal of photogrammetry and remote sensing, vol 183 (January 2022)PermalinkPermalinkComparative analysis for methods of building digital elevation models from topographic maps using geoinformation technologies / Vadim Belenok in Geodesy and cartography, vol 47 n° 4 (December 2021)PermalinkUn désordre complexe à modéliser / Laurent Polidori in Géomètre, n° 2197 (décembre 2021)PermalinkModelling bark volume for six commercially important tree species in France: assessment of models and application at regional scale / Rodolphe Bauer in Annals of Forest Science, vol 78 n° 4 (December 2021)PermalinkParticle swarm optimization based water index (PSOWI) for mapping the water extents from satellite images / Mohammad Hossein Gamshadzaei in Geocarto international, vol 36 n° 20 ([01/12/2021])PermalinkWhat is the impact of tectonic plate movement on country size? A long-term forecast / Kamil Maciuk in Remote sensing, vol 13 n° 23 (December-1 2021)PermalinkA method of extracting high-accuracy elevation control points from ICESat-2 altimetry data / Binbin Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)PermalinkBinary space partitioning visibility tree for polygonal and environment light rendering / Hiroki Okuno in The Visual Computer, vol 37 n° 9 - 11 (September 2021)PermalinkMetaheuristics for the positioning of 3D objects based on image analysis of complementary 2D photographs / Arnaud Flori in Machine Vision and Applications, vol 32 n° 5 (September 2021)PermalinkQuantifying coherence between TDM90, SRTM90 and ASTER90 / Umut Gunes Sefercik in Geocarto international, vol 36 n° 15 ([15/08/2021])PermalinkScalable surface reconstruction with Delaunay-Graph neural networks / Raphaël Sulzer in Computer graphics forum, vol 40 n° 5 (2021)PermalinkStructure-aware indoor scene reconstruction via two levels of abstraction / Hao Fang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)Permalink