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Titre : Multi-layer modeling of dense vegetation from aerial LiDAR scans Type de document : Article/Communication Auteurs : Ekaterina Kalinicheva , Auteur ; Loïc Landrieu , Auteur ; Clément Mallet , Auteur ; Nesrine Chehata , Auteur Editeur : Computer vision foundation CVF Année de publication : 2022 Projets : 1-Pas de projet / Conférence : EarthVision 2022, Large Scale Computer Vision for Remote Sensing Imagery, workshop joint to CVPR 2022 19/06/2022 24/06/2022 New Orleans Louisiane - Etats-Unis OA Proceedings Importance : pp 1341 - 1350 Format : 21 x 30 cm Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] canopée
[Termes IGN] carte d'occupation du sol
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] étage de végétation
[Termes IGN] foresterie
[Termes IGN] maillage
[Termes IGN] parcelle forestière
[Termes IGN] reconstruction d'objet
[Termes IGN] segmentation d'image
[Termes IGN] semis de pointsRésumé : (auteur) The analysis of the multi-layer structure of wild forests is an important challenge of automated large-scale forestry. While modern aerial LiDARs offer geometric information across all vegetation layers, most datasets and methods focus only on the segmentation and reconstruction of the top of canopy. We release WildForest3D, which consists of 29 study plots and over 2000 individual trees across 47 000m2 with dense 3D annotation, along with occupancy and height maps for 3 vegetation layers: ground vegetation, understory, and overstory. We propose a 3D deep net- work architecture predicting for the first time both 3D point- wise labels and high-resolution layer occupancy rasters simultaneously. This allows us to produce a precise estimation of the thickness of each vegetation layer as well as the corresponding watertight meshes, therefore meeting most forestry purposes. Both the dataset and the model are released in open access: https://github.com/ ekalinicheva/multi_layer_vegetation. Numéro de notice : C2022-007 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers CVF Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/CVPRW56347.2022.00140 Date de publication en ligne : 25/04/2022 En ligne : https://arxiv.org/abs/2204.11620 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100509 Detection of periodic displacements of shell structures with edges using spline surfaces, meshes and point clouds / Grzegorz Lenda in Reports on geodesy and geoinformatics, vol 112 n° 1 (December 2021)
[article]
Titre : Detection of periodic displacements of shell structures with edges using spline surfaces, meshes and point clouds Type de document : Article/Communication Auteurs : Grzegorz Lenda, Auteur ; Katarzyna Abrachamowicz, Auteur Année de publication : 2021 Article en page(s) : pp 27 - 33 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] déformation d'édifice
[Termes IGN] fonction spline
[Termes IGN] maillage
[Termes IGN] semis de points
[Termes IGN] Triangulated Irregular NetworkRésumé : (auteur) This research paper tackles the problem of determining displacements of complex-shaped shell structures, measured periodically using laser scanning. Point clouds obtained during different measurement epochs can be compared with each other directly or they can be converted into continuous models in the form of a triangle mesh or smooth patches (spline functions). The accuracy of the direct comparison of point clouds depends on the scanning density, while the accuracy of comparing the point cloud to the model depends on approximation errors that are formed during its creation. Modelling using triangle meshes flattens the local structure of the object compared to the spline model. However, if the shell has edges in its structure, their exact representation by spline models is impossible due to the undulations of functions along them. Edges can also be distorted by the mesh model by their chamfering with transverse triangles. These types of surface modelling errors can lead to the generation of pseudo-deformation of the structure, which is difficult to distinguish from real deformation. In order to assess the possibility of correct determination of deformation using the above-mentioned methods, laser scanning of a complex shell structure in two epochs was performed. Then, modelling and comparison of the results of periodic measurements were carried out. As a result of the research, advantages and disadvantages of each method were identified. It was noticed that none of the methods made it possible to correctly represent all deformations while suppressing pseudo-deformation. However, the combination of their best qualities made it possible to determine the actual deformation of the structure. Numéro de notice : A2021-962 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.2478/rgg-2021-0005 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.2478/rgg-2021-0005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100114
in Reports on geodesy and geoinformatics > vol 112 n° 1 (December 2021) . - pp 27 - 33[article]Structure-aware indoor scene reconstruction via two levels of abstraction / Hao Fang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)
[article]
Titre : Structure-aware indoor scene reconstruction via two levels of abstraction Type de document : Article/Communication Auteurs : Hao Fang, Auteur ; Cihui Pan, Auteur ; Hui Huang, Auteur Année de publication : 2021 Article en page(s) : pp 155 - 170 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image optique
[Termes IGN] maillage
[Termes IGN] maille triangulaire
[Termes IGN] niveau d'abstraction
[Termes IGN] polygone
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] scène intérieureRésumé : (auteur) In this paper, we propose a novel approach that reconstructs the indoor scene in a structure-aware manner and produces two meshes with different levels of abstraction. To be precise, we start from the raw triangular mesh of indoor scene and decompose it into two parts: structure and non-structure objects. On the one hand, structure objects are defined as significant permanent parts in the indoor environment such as floors, ceilings and walls. In the proposed algorithm, structure objects are abstracted by planar primitives and assembled into a polygonal structure mesh. This step produces a compact structure-aware watertight model that decreases the complexity of original mesh by three orders of magnitude. On the other hand, non-structure objects are movable objects in the indoor environment such as furniture and interior decoration. Meshes of these objects are repaired and simplified according to their relationship with respect to structure primitives. Finally, the union of all the non-structure meshes and structure mesh comprises the scene mesh. Note that structure mesh and scene mesh preserve various levels of abstraction and can be used for different applications according to user preference. Our experiments on both LIDAR and RGBD data scanned from simple to large scale indoor scenes indicate that the proposed framework generates structure-aware results while being robust and scalable. It is also compared qualitatively and quantitatively against popular mesh approximation, floorplan generation and piecewise-planar surface reconstruction methods to demonstrate its performance. Numéro de notice : A2021-561 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.06.007 Date de publication en ligne : 23/06/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.06.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98119
in ISPRS Journal of photogrammetry and remote sensing > vol 178 (August 2021) . - pp 155 - 170[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021081 SL Revue Centre de documentation Revues en salle Disponible 081-2021083 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021082 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt 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)
[article]
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 IGN] champ aléatoire de Markov
[Termes IGN] données lidar
[Termes IGN] espace intérieur
[Termes IGN] maillage
[Termes IGN] programmation linéaire
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] vectorisationRésumé : (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
in ISPRS Journal of photogrammetry and remote sensing > vol 177 (July 2021) . - pp 57 - 74[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021071 SL Revue Centre de documentation Revues en salle Disponible 081-2021073 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021072 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Structure-aware completion of photogrammetric meshes in urban road environment / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)
[article]
Titre : Structure-aware completion of photogrammetric meshes in urban road environment Type de document : Article/Communication Auteurs : Qing Zhu, Auteur ; Qisen Shang, Auteur ; Han Hu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 56 - 70 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] détection de partie cachée
[Termes IGN] espace urbain
[Termes IGN] image aérienne oblique
[Termes IGN] maillage
[Termes IGN] modélisation 3D
[Termes IGN] reconstruction de route
[Termes IGN] réseau routier
[Termes IGN] texture d'image
[Termes IGN] véhicule automobileRésumé : (auteur) Photogrammetric mesh models obtained from aerial oblique images have been widely used for urban reconstruction. However, photogrammetric meshes suffer from severe texture problems, particularly in typical road areas, owing to occlusion. This paper proposes a structure-aware completion approach to improve mesh quality by seamlessly removing undesired vehicles. Specifically, a discontinuous texture atlas is first integrated into a continuous screen space by rendering trough a graphics pipeline. The rendering also records the necessary mapping for deintegration to the original texture atlas after editing. Vehicle regions are masked by a standard object detection approach, namely, Faster RCNN. Subsequently, the masked regions are completed, guided by the linear structures and regularities in the road region; this is implemented based on PatchMatch. Finally, the completed rendered image is deintegrated to the original texture atlas, and the triangles for the vehicles are also flattened so that improved meshes can be obtained. Experimental evaluation and analysis are conducted on three datasets, which were captured with different sensors and ground sample distances. The results demonstrate that the proposed method can produce quite realistic meshes after removing the vehicles. The structure-aware completion approach for road regions outperforms popular image completion methods, and an ablation study further confirms the effectiveness of the linear guidance. It should be noted that the proposed method can also handle tiled mesh models for large-scale scenes. Code and datasets are available at the project website. Numéro de notice : A2021-263 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.02.010 Date de publication en ligne : 11/03/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.02.010 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97312
in ISPRS Journal of photogrammetry and remote sensing > vol 175 (May 2021) . - pp 56 - 70[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021051 SL Revue Centre de documentation Revues en salle Disponible 081-2021052 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt 081-2021053 DEP-RECP Revue Saint-Mandé Dépôt en unité Exclu du prêt Dynamic human body reconstruction and motion tracking with low-cost depth cameras / Kangkan Wang in The Visual Computer, vol 37 n° 3 (March 2021)PermalinkMinimum-error world map projections defined by polydimensional meshes / Justin H. Kunimune in International journal of cartography, vol 7 n° 1 (March 2021)PermalinkPermalinkLearning-based representations and methods for 3D shape analysis, manipulation and reconstruction / Marie-Julie Rakotosaona (2021)PermalinkPlanimetric simplification and lexicographic optimal chains for 3D urban scene reconstruction / Julien Vuillamy (2021)Permalink3D hand mesh reconstruction from a monocular RGB image / Hao Peng in The Visual Computer, vol 36 n° 10 - 12 (October 2020)PermalinkLeveraging photogrammetric mesh models for aerial-ground feature point matching toward integrated 3D reconstruction / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkPhotogrammetric determination of 3D crack opening vectors from 3D displacement fields / Frank Liebold in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkAnalyse hydrologique du réseau de drainage de la zone sud de la métropole nantaise pour une meilleure gestion des eaux pluviales / Anna Guézénoc (2020)PermalinkPermalink