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appariement de données localiséesSynonyme(s)mise en correspondance de données géographiques appariement d'objets géographiques |
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Dynamic human body reconstruction and motion tracking with low-cost depth cameras / Kangkan Wang in The Visual Computer, vol 37 n° 3 (March 2021)
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[article]
Titre : Dynamic human body reconstruction and motion tracking with low-cost depth cameras Type de document : Article/Communication Auteurs : Kangkan Wang, Auteur ; Guofeng Zhang, Auteur ; Jian Yang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 603 - 618 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de formes
[Termes IGN] déformation de projection
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] filtrage spatiotemporel
[Termes IGN] maillage
[Termes IGN] modèle dynamique
[Termes IGN] modélisation 3D
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'objet
[Termes IGN] squelettisationRésumé : (auteur) We present a novel approach for dynamic human body reconstruction and motion tracking using low-cost depth cameras. Our reconstruction system is able to produce a sequence of dynamic 3D human body models from the noisy input depth data. To accurately align the template model with noisy input data, we combine skeleton-driven deformation and mesh deformation techniques to enhance the registration robustness to depth missing, occlusions, and severe noise. In addition, a novel data-driven 3D human body model is introduced to efficiently reconstruct human body models with wide shape and pose variations only using a limited number of training databases with standard standing pose. We perform quantitative and qualitative experiments to evaluate our method and compare it with other methods for body reconstruction on both synthetic and real datasets. Experimental results demonstrate the effectiveness of the proposed approach. Numéro de notice : A2021-341 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-020-01826-4 Date de publication en ligne : 26/02/2020 En ligne : https://doi.org/10.1007/s00371-020-01826-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97579
in The Visual Computer > vol 37 n° 3 (March 2021) . - pp 603 - 618[article]Enhanced trajectory estimation of mobile laser scanners using aerial images / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)
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Titre : Enhanced trajectory estimation of mobile laser scanners using aerial images Type de document : Article/Communication Auteurs : Zille Hussnain, Auteur ; Sander J. Oude Elberink, Auteur ; M. George Vosselman, Auteur Année de publication : 2021 Article en page(s) : pp 66 - 78 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] appariement de points
[Termes IGN] atténuation du signal
[Termes IGN] balayage laser
[Termes IGN] canyon urbain
[Termes IGN] centrale inertielle
[Termes IGN] données lidar
[Termes IGN] erreur
[Termes IGN] image captée par drone
[Termes IGN] mesurage par GNSS
[Termes IGN] semis de points
[Termes IGN] trajectoire (véhicule non spatial)
[Termes IGN] trajet multipleRésumé : (auteur) Multipath effects and signal obstruction by buildings in urban canyons can lead to inaccurate GNSS measurements and therefore errors in the estimated trajectory of Mobile Laser Scanning (MLS) systems; consequently, derived point clouds are distorted and lose spatial consistency. We obtain decimetre-level trajectory accuracy making use of corresponding points between the MLS data and aerial images with accurate exterior orientations instead of using ground control points. The MLS trajectory is estimated based on observation equations resulting from these corresponding points, the original IMU observations, and soft constraints on the pitch and yaw rotations of the vehicle. We analyse the quality of the trajectory enhancement under several conditions where the experiments were designed to test the influence of the number and quality of corresponding points and to test different settings for a B-spline representation of the vehicle trajectory. The method was tested on two independently acquired MLS datasets in Rotterdam by enhancing the trajectories and evaluating them using checkpoints. The RMSE values of the original GNSS/IMU based Kalman filter results at the checkpoints were 0.26 m, 0.30 m, and 0.47 m for the X-, Y- and Z-coordinates in the first dataset and 1.10 m, 1.51 m, and 1.81 m in the second dataset. The latter dataset was recorded with a lower quality IMU in an area with taller buildings. After trajectory adjustment these RMSE values were reduced to 0.09 m, 0.11 m, and 0.16 m for the first dataset and 0.12 m, 0.14 m, and 0.18 m for the second dataset. The results confirmed that, if sufficient tie points between the point cloud and aerial imagery are available, the method supports geo-referencing of MLS point clouds in urban canyons with a near-decimetre accuracy. Numéro de notice : A2021-102 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.005 Date de publication en ligne : 17/01/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.005 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96877
in ISPRS Journal of photogrammetry and remote sensing > vol 173 (March 2021) . - pp 66 - 78[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021031 SL Revue Centre de documentation Revues en salle Disponible 081-2021033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Feature detection and description for image matching: from hand-crafted design to deep learning / Lin Chen in Geo-spatial Information Science, vol 24 n° 1 (March 2021)
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Titre : Feature detection and description for image matching: from hand-crafted design to deep learning Type de document : Article/Communication Auteurs : Lin Chen, Auteur ; Franz Rottensteiner, Auteur ; Christian Heipke, Auteur Année de publication : 2021 Article en page(s) : pp 58 - 74 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement automatique
[Termes IGN] appariement d'images
[Termes IGN] appariement de formes
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image aérienne oblique
[Termes IGN] orientation d'image
[Termes IGN] SIFT (algorithme)Résumé : (Auteur) In feature based image matching, distinctive features in images are detected and represented by feature descriptors. Matching is then carried out by assessing the similarity of the descriptors of potentially conjugate points. In this paper, we first shortly discuss the general framework. Then, we review feature detection as well as the determination of affine shape and orientation of local features, before analyzing feature description in more detail. In the feature description review, the general framework of local feature description is presented first. Then, the review discusses the evolution from hand-crafted feature descriptors, e.g. SIFT (Scale Invariant Feature Transform), to machine learning and deep learning based descriptors. The machine learning models, the training loss and the respective training data of learning-based algorithms are looked at in more detail; subsequently the various advantages and challenges of the different approaches are discussed. Finally, we present and assess some current research directions before concluding the paper. Numéro de notice : A2021-297 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1843376 Date de publication en ligne : 17/11/2020 En ligne : https://doi.org/10.1080/10095020.2020.1843376 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97379
in Geo-spatial Information Science > vol 24 n° 1 (March 2021) . - pp 58 - 74[article]Toward a yearly country-scale CORINE land-cover map without using images: A map translation approach / Luc Baudoux in Remote sensing, Vol 13 n° 6 (March 2021)
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Titre : Toward a yearly country-scale CORINE land-cover map without using images: A map translation approach Type de document : Article/Communication Auteurs : Luc Baudoux , Auteur ; Jordi Inglada, Auteur ; Clément Mallet
, Auteur
Année de publication : 2021 Projets : AI4GEO / , MAESTRIA / Mallet, Clément Article en page(s) : n° 1060 - 32 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] appariement sémantique
[Termes IGN] apprentissage dirigé
[Termes IGN] carte d'occupation du sol
[Termes IGN] changement d'occupation du sol
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] Corine Land Cover
[Termes IGN] détection de changement
[Termes IGN] image à haute résolution
[Termes IGN] inférence
[Termes IGN] mise à jour automatique
[Termes IGN] mise à jour de base de donnéesRésumé : (Auteur) CORINE Land-Cover (CLC) and its by-products are considered as a reference baseline for land-cover mapping over Europe and subsequent applications. CLC is currently tediously produced each six years from both the visual interpretation and the automatic analysis of a large amount of remote sensing images. Observing that various European countries regularly produce in parallel their own land-cover country-scaled maps with their own specifications, we propose to directly infer CORINE Land-Cover from an existing map, therefore steadily decreasing the updating time-frame. No additional remote sensing image is required. In this paper, we focus more specifically on translating a country-scale remote sensed map, OSO (France), into CORINE Land Cover, in a supervised way. OSO and CLC not only differ in nomenclature but also in spatial resolution. We jointly harmonize both dimensions using a contextual and asymmetrical Convolution Neural Network with positional encoding. We show for various use cases that our method achieves a superior performance than the traditional semantic-based translation approach, achieving an 81% accuracy over all of France, close to the targeted 85% accuracy of CLC. Numéro de notice : A2021-244 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13061060 Date de publication en ligne : 11/03/2021 En ligne : https://dx.doi.org/10.3390/rs13061060 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97311
in Remote sensing > Vol 13 n° 6 (March 2021) . - n° 1060 - 32 p.[article]An anchor-based graph method for detecting and classifying indoor objects from cluttered 3D point clouds / Fei Su in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)
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Titre : An anchor-based graph method for detecting and classifying indoor objects from cluttered 3D point clouds Type de document : Article/Communication Auteurs : Fei Su, Auteur ; Haihong Zhu, Auteur ; Taoyi Chen, Auteur Année de publication : 2021 Article en page(s) : pp 114 - 131 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] adjacence
[Termes IGN] appariement de graphes
[Termes IGN] arc
[Termes IGN] bloc d'ancrage
[Termes IGN] classification orientée objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] jeu de données localisées
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] noeud
[Termes IGN] objet 3D
[Termes IGN] orientation
[Termes IGN] positionnement en intérieur
[Termes IGN] semis de pointsRésumé : (auteur) Most of the existing 3D indoor object classification methods have shown impressive achievements on the assumption that all objects are oriented in the upward direction with respect to the ground. To release this assumption, great effort has been made to handle arbitrarily oriented objects in terrestrial laser scanning (TLS) point clouds. As one of the most promising solutions, anchor-based graphs can be used to classify freely oriented objects. However, this approach suffers from missing anchor detection since valid detection relies heavily on the completeness of an anchor’s point clouds and is sensitive to missing data. This paper presents an anchor-based graph method to detect and classify arbitrarily oriented indoor objects. The anchors of each object are extracted by the structurally adjacent relationship among parts instead of the parts’ geometric metrics. In the case of adjacency, an anchor can be correctly extracted even with missing parts since the adjacency between an anchor and other parts is retained irrespective of the area extent of the considered parts. The best graph matching is achieved by finding the optimal corresponding node-pairs in a super-graph with fully connecting nodes based on maximum likelihood. The performances of the proposed method are evaluated with three indicators (object precision, object recall and object F1-score) in seven datasets. The experimental tests demonstrate the effectiveness of dealing with TLS point clouds, RGBD point clouds and Panorama RGBD point clouds, resulting in performance scores of approximately 0.8 for object precision and recall and over 0.9 for chair precision and table recall. Numéro de notice : A2021-087 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.12.007 Date de publication en ligne : 29/12/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.12.007 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96852
in ISPRS Journal of photogrammetry and remote sensing > vol 172 (February 2021) . - pp 114 - 131[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 081-2021021 SL Revue Centre de documentation Revues en salle Disponible 081-2021022 DEP-RECF Revue Nancy Bibliothèque Nancy IFN Exclu du prêt A points of interest matching method using a multivariate weighting function with gradient descent optimization / Zhou Yang in Transactions in GIS, Vol 25 n° 1 (February 2021)
PermalinkEnjeux et méthodes d’un liage de référentiels géographiques : l’exemple du projet de recherche ALEGORIA / Clara Lelièvre (2021)
PermalinkHidden Markov map matching based on trajectory segmentation with heading homogeneity / Ge Cui in Geoinformatica, vol 25 n° 1 (January 2021)
PermalinkImage matching from handcrafted to deep features: A survey / Jiayi Ma in International journal of computer vision, vol 29 n° 1 (January 2021)
PermalinkPermalinkRoad network simplification for location-based services / Abdeltawab M. Hendawi in Geoinformatica, vol 24 n° 4 (October 2020)
PermalinkGuided feature matching for multi-epoch historical image blocks pose estimation / Lulin Zhang in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 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)
PermalinkSketch maps for searching in spatial data / Ali Zare Zardiny in Transactions in GIS, Vol 24 n° 3 (June 2020)
PermalinkHow much do we learn from addresses? On the syntax, semantics and pragmatics of addressing systems / Ali Javidaneh in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)
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