Descripteur
Termes IGN > géomatique > infrastructure mondiale des données localisées > qualité des données > cohérence des données > cohérence géométrique
cohérence géométrique |
Documents disponibles dans cette catégorie (32)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
![Tris disponibles](./images/orderby_az.gif)
Etendre la recherche sur niveau(x) vers le bas
Road-network-based fast geolocalization / Yongfei Li in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
![]()
[article]
Titre : Road-network-based fast geolocalization Type de document : Article/Communication Auteurs : Yongfei Li, Auteur ; Dongfang Yang, Auteur ; Shisheng Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 6065 - 6076 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carrefour
[Termes IGN] carte routière
[Termes IGN] cohérence géométrique
[Termes IGN] géolocalisation
[Termes IGN] image aérienne
[Termes IGN] réseau routier
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] superposition d'images
[Termes IGN] transformation homographique
[Termes IGN] zone urbaineRésumé : (auteur) In this article, a road-network-based geolocalization method is proposed. We match roads in the onboard images to the reference road vector map, and realize successful localization over areas as large as a whole city. The road network matching problem is treated as a point cloud registration problem under the homography transformation and solved under the hypothesize-and-test framework. To tackle the point cloud registration problem, a global projective-invariant feature is proposed, which consists of two road intersections augmented with their tangents. In addition, we propose the necessary conditions for the features to match. This can reduce the candidate matching features, thus accelerating the search to a great extent. These matching candidates are first “filtered” with the model consistency check in parameter space and then tested with similarity metrics to identify the correct transformation. The experiments show that our method can localize an aerial image over an area larger than 1000 km 2 within several seconds on a single CPU. Our code can be found at: https://github.com/FlyAlCode/RCLGeolocalization-2.0 . Numéro de notice : A2021-532 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3011034 Date de publication en ligne : 18/08/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3011034 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97989
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 7 (July 2021) . - pp 6065 - 6076[article]ALERT: adversarial learning with expert regularization using Tikhonov operator for missing band reconstruction / Litu Rout in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)
![]()
[article]
Titre : ALERT: adversarial learning with expert regularization using Tikhonov operator for missing band reconstruction Type de document : Article/Communication Auteurs : Litu Rout, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage dirigé
[Termes IGN] bande spectrale
[Termes IGN] cohérence géométrique
[Termes IGN] correction d'image
[Termes IGN] dégradation d'image
[Termes IGN] image Worldview
[Termes IGN] pollution acoustique
[Termes IGN] qualité d'image
[Termes IGN] régularisation de TychonoffRésumé : (auteur) The Earth observation using remote sensing is one of the most important technologies to assimilate key attributes about the Earth’s surface. To achieve tangible consequence, the internal building blocks of such a complex system must operate flawlessly. However, due to a dynamically changing environment, degradation in sensor electronics, and extreme weather condition remotely sensed images often miss essential information. As the sensors operate over several years in space the likelihood of sensor degradation persists. This results in commonly observed issues, such as stripe noise, missing partial data, and missing band. Various ground-based solutions have been developed to address these technological bottlenecks individually. In this article, we devise a method, which we call ALERT, to tackle missing band reconstruction. The proposed method reconstructs the missing band with the sole supervision of spectral and spatial priors. We compare the proposed framework with state-of-the-art methods and show compelling improvement both qualitatively and quantitatively. We provide both theoretical and empirical evidence of better performance by regularized adversarial learning as compared to complete supervision. Furthermore, we propose a new residual-dense-block (RDB) module to preserve geometric fidelity and assist in efficient gradient flow. We show that ALERT captures essential features such that the spatial and spectral characteristics of the reconstructed band remains preserved. To critically analyze the generalization we test the performance on two different satellite data sets: Resourcesat-2A and WorldView-2. As per our extensive experimentation, the proposed method achieves 20.72%, 13.81%, 1.05%, 15.91%, and 2.94% improvement in the root mean square error (RMSE), SAM, SSIM, PSNR, and SRE, respectively, over the state-of-the-art model. Numéro de notice : A2020-285 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2963818 Date de publication en ligne : 16/01/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2963818 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95108
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 6 (June 2020)[article]Consistency and analysis of ionospheric observables obtained from three precise point positioning models / Yan Xiang in Journal of geodesy, vol 93 n° 8 (August 2019)
![]()
[article]
Titre : Consistency and analysis of ionospheric observables obtained from three precise point positioning models Type de document : Article/Communication Auteurs : Yan Xiang, Auteur ; Yang Gao, Auteur ; Junbo Shi, Auteur ; Chaoqian Xu, Auteur Année de publication : 2019 Article en page(s) : pp 1161–1170 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] analyse comparative
[Termes IGN] cohérence géométrique
[Termes IGN] erreur de positionnement
[Termes IGN] erreur en altitude
[Termes IGN] erreur systématique
[Termes IGN] mesurage de phase
[Termes IGN] modèle ionosphérique
[Termes IGN] positionnement différentiel
[Termes IGN] positionnement ponctuel précis
[Termes IGN] propagation ionosphériqueRésumé : (auteur) Ionospheric observables based on Global Navigation Satellite System can be obtained by a variety of approaches. The most widely used one is the geometry-free combination of carrier-phase smoothed code measurements. This method, however, introduces leveling errors that substantially degrade the performance of ionospheric modeling and bias estimation. To reduce leveling errors, precise point positioning (PPP) model is preferred for obtaining the ionospheric observables. We aim to investigate whether the ionospheric observables obtained from three different PPP models are consistent and how the PPP-based ionospheric observables relates to the smoothed code method. The paper begins by formulating the ionospheric observables. We then explain the statistical evaluation methods used for analyzing the bias terms derived from these methods and assessing the leveling errors from the carrier-phase smoothed code method. Numerical analysis is then conducted to compare the bias terms in the ionospheric observables and evaluate the leveling errors. The ionospheric observables based on the three PPP models show strong consistency. Compared to leveling errors in the carrier-phase smoothed code method, the leveling errors using the uncombined PPP model are significantly reduced up to five times. Numéro de notice : A2019-384 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-019-01233-1 Date de publication en ligne : 12/02/2019 En ligne : https://doi.org/10.1007/s00190-019-01233-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93463
in Journal of geodesy > vol 93 n° 8 (August 2019) . - pp 1161–1170[article]Complete 3D scene parsing from an RGBD image / Chuhang Zou in International journal of computer vision, vol 127 n° 2 (February 2019)
![]()
[article]
Titre : Complete 3D scene parsing from an RGBD image Type de document : Article/Communication Auteurs : Chuhang Zou, Auteur ; Ruiqi Guo, Auteur ; Zhizhong Li, Auteur ; Derek Hoiem, Auteur Année de publication : 2019 Article en page(s) : pp 143 - 162 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] cohérence géométrique
[Termes IGN] compréhension de l'image
[Termes IGN] image isolée
[Termes IGN] image RVB
[Termes IGN] reconstruction d'objet
[Termes IGN] scène 3DRésumé : (Auteur) One major goal of vision is to infer physical models of objects, surfaces, and their layout from sensors. In this paper, we aim to interpret indoor scenes from one RGBD image. Our representation encodes the layout of orthogonal walls and the extent of objects, modeled with CAD-like 3D shapes. We parse both the visible and occluded portions of the scene and all observable objects, producing a complete 3D parse. Such a scene interpretation is useful for robotics and visual reasoning, but difficult to produce due to the well-known challenge of segmentation, the high degree of occlusion, and the diversity of objects in indoor scenes. We take a data-driven approach, generating sets of potential object regions, matching to regions in training images, and transferring and aligning associated 3D models while encouraging fit to observations and spatial consistency. We use support inference to aid interpretation and propose a retrieval scheme that uses convolutional neural networks to classify regions and retrieve objects with similar shapes. We demonstrate the performance of our method on our newly annotated NYUd v2 dataset (Silberman et al., in: Computer vision-ECCV, 2012, pp 746–760, 2012) with detailed 3D shapes. Numéro de notice : A2018-598 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-018-1133-z Date de publication en ligne : 21/11/2018 En ligne : https://doi.org/10.1007/s11263-018-1133-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92525
in International journal of computer vision > vol 127 n° 2 (February 2019) . - pp 143 - 162[article]Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree / José Antonio Martin-Jimenez in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)
![]()
[article]
Titre : Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree Type de document : Article/Communication Auteurs : José Antonio Martin-Jimenez, Auteur ; Santiago Zazo, Auteur ; José Juan Arranz Justel, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 334 - 346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] accident de la route
[Termes IGN] arbre de décision
[Termes IGN] cohérence géométrique
[Termes IGN] données GNSS
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Espagne
[Termes IGN] extraction du réseau routier
[Termes IGN] indice de risque
[Termes IGN] lidar mobile
[Termes IGN] raisonnement
[Termes IGN] sécurité routière
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] triangulation de DelaunayRésumé : (auteur) Safe roads are a necessity for any society because of the high social costs of traffic accidents. This challenge is addressed by a novel methodology that allows us to evaluate road safety from Mobile LiDAR System data, taking advantage of the road alignment due to its influence on the accident rate. Automation is obtained through an inductive reasoning process based on a decision tree that provides a potential risk assessment. To achieve this, a 3D point cloud is classified by an iterative and incremental algorithm based on a 2.5D and 3D Delaunay triangulation, which apply different algorithms sequentially. Next, an automatic extraction process of road horizontal alignment parameters is developed to obtain geometric consistency indexes, based on a joint triple stability criterion. Likewise, this work aims to provide a powerful and effective preventive and/or predictive tool for road safety inspections. The proposed methodology was implemented on three stretches of Spanish roads, each with different traffic conditions that represent the most common road types. The developed methodology was successfully validated through as-built road projects, which were considered as “ground truth.” Numéro de notice : A2018-541 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.10.004 Date de publication en ligne : 21/10/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.10.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91565
in ISPRS Journal of photogrammetry and remote sensing > vol 146 (December 2018) . - pp 334 - 346[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2018131 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018133 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018132 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Geometrical consistency voting strategy for outlier detection in image matching / Luping Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)
PermalinkQualitative spatial logics for buffered geometries / Heshan Du in Journal of Artificial Intelligence Research, vol 56 (May - August 2016)
PermalinkThe variants of an LOD of a 3D building model and their influence on spatial analyses / Filip Biljecki in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)
PermalinkPermalinkAn automated approach for the conflation of vector parcel map with imagery / Wenbo Song in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 6 (June 2013)
PermalinkA deterministic method to integrate triangular meshes of different resolution / Giorgio Agugiaro in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
PermalinkRoad network extraction in suburban areas / A. Grote in Photogrammetric record, vol 27 n° 137 (March - May 2012)
PermalinkProvably correct and complete transaction rules for updating 3D city models / G. Groger in Geoinformatica, vol 16 n° 1 (January 2012)
PermalinkMulti close-range image matching based on a self-adaptive triangle constraint / Q. Zhu in Photogrammetric record, vol 25 n° 132 (December 2010 - February 2011)
PermalinkSegmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)
Permalink