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Provably consistent distributed Delaunay triangulation / Mathieu Brédif in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 195 - 202 Titre : Provably consistent distributed Delaunay triangulation Type de document : Article/Communication Auteurs : Mathieu Brédif , Auteur ; Laurent Caraffa , Auteur ; Murat Yirci, Auteur ; Pooran Memari, Auteur Année de publication : 2020 Projets : IQmulus / Métral, Claudine Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 195 - 202 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] géomètrie algorithmique [Termes IGN] informatique en nuage [Termes IGN] semis de points [Termes IGN] Spark [Termes IGN] traitement de semis de points [Termes IGN] triangulation de Delaunay Résumé : (Auteur) This paper deals with the distributed computation of Delaunay triangulations of massive point sets, mainly motivated by the needs of a scalable out-of-core surface reconstruction workflow from massive urban LIDAR datasets. Such a data often corresponds to a huge point cloud represented through a set of tiles of relatively homogeneous point sizes. This will be the input of our algorithm which will naturally partition this data across multiple processing elements. The distributed computation and communication between processing elements is orchestrated efficiently through an uncentralized model to represent, manage and locally construct the triangulation corresponding to each tile. Initially inspired by the star splaying approach, we review the Tile\& Merge algorithm for computing Distributed Delaunay Triangulations on the cloud, provide a theoretical proof of correctness of this algorithm, and analyse the performance of our Spark implementation in terms of speedup and strong scaling in both synthetic and real use case datasets. A HPC implementation (e.g. using MPI), left for future work, would benefit from its more efficient message passing paradigm but lose the robustness and failure resilience of our Spark approach. Numéro de notice : A2020-410 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-195-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-195-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94979 [article]

Guided 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)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 127 - 134 Titre : Guided feature matching for multi-epoch historical image blocks pose estimation Type de document : Article/Communication Auteurs : Lulin Zhang , Auteur ; Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur Année de publication : 2020 Projets : DISRUPT / Klinger, Yann Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 127 - 134 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] analyse comparative [Termes IGN] appariement d'images [Termes IGN] appariement de points [Termes IGN] bloc d'images [Termes IGN] estimation de pose [Termes IGN] Hérault (34) [Termes IGN] image aérienne [Termes IGN] mesure de similitude multidimensionnelle [Termes IGN] modèle numérique de surface [Termes IGN] point d'appui [Termes IGN] points homologues [Termes IGN] SIFT (algorithme) Résumé : (Auteur) Historical aerial imagery plays an important role in providing unique information about evolution of our landscapes. It possesses many positive qualities such as high spatial resolution, stereoscopic configuration and short time interval. Self-calibration reamains a main bottleneck for achieving the intrinsic value of historical imagery, as it involves certain underdeveloped research points such as detecting inter-epoch tie-points. In this research, we present a novel algorithm to detecting inter-epoch tie-points in historical images which do not rely on any auxiliary data. Using SIFT-detected keypoints we perform matching across epochs by interchangeably estimating and imposing that points follow two mathematical models: at first a 2D spatial similarity, then a 3D spatial similarity. We import GCPs to quantitatively evaluate our results with Digital Elevation Models (DEM) of differences (abbreviated as DoD) in absolute reference frame, and compare the results of our method with other 2 methods that use either the traditional SIFT or few virtual GCPs. The experiments show that far more correct inter-epoch tie-points can be extracted with our guided technique. Qualitative and quantitative results are reported. Numéro de notice : A2020-411 Affiliation des auteurs : LASTIG MATIS (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-127-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-127-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95081 [article]

Geometric distortion of historical images for 3D visualization / Evelyn Paiz-Reyes in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 649 - 655 Titre : Geometric distortion of historical images for 3D visualization Type de document : Article/Communication Auteurs : Evelyn Paiz-Reyes , Auteur ; Mathieu Brédif , Auteur ; Sidonie Christophe , Auteur Année de publication : 2020 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 649 - 655 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] base de données historiques [Termes IGN] distorsion d'image [Termes IGN] image numérisée [Termes IGN] modèle de déformation des images [Termes IGN] rendu (géovisualisation) [Termes IGN] scène 3D [Termes IGN] visualisation 3D [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Archivists, historians and national mapping agencies, among others, are archiving large datasets of historical photographs. Nevertheless, the capturing devices used to acquire these images possessed a diversity of effects that influenced the quality of the final resulting picture, e.g. geometric distortion, chromatic aberration, depth of field variation, etc. This paper examines singularly the topic of geometric distortion for a co-visualization of historical photos within a 3D model of the photographed scene. A distortion function of an image is ordinarily estimated only on the image domain by adjusting its parameters to observations of point correspondences. This mathematical function may exhibit overfits, oscillations or may not be well defined outside of this domain. The contribution of this work is the description of a distortion model defined on the whole undistorted image plane. We extrapolate the distortion estimated only on the image domain and then transfer this distortion information to the view of the 3D scene. This enables to look at the scene through an estimated camera and zoom out to see the context around the original photograph with a well-defined and behaved distortion. These findings may be a significant addition to the overall purpose of creating innovative ways to examine and visualize old photographs. Numéro de notice : A2020-468 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-649-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-649-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95537 [article]

A worldwide 3D GCP database inherited from 20 years of massive multi-satellite observations / Laure Chandelier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 15 - 23 Titre : A worldwide 3D GCP database inherited from 20 years of massive multi-satellite observations Type de document : Article/Communication Auteurs : Laure Chandelier , Auteur ; Laurent Coeurdevey, Auteur ; Sébastien Bosch, Auteur ; Pascal Favé, Auteur ; Roland Gachet, Auteur ; Alain Orsoni , Auteur ; Thomas Tilak , Auteur ; Alexis Barot, Auteur Année de publication : 2020 Projets : 1-Pas de projet / Gouet-Brunet, Valérie Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 15 - 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] base de données d'images [Termes IGN] compensation par bloc [Termes IGN] données localisées de référence [Termes IGN] formatage [Termes IGN] image à très haute résolution [Termes IGN] image multi sources [Termes IGN] image satellite [Termes IGN] image SPOT 6 [Termes IGN] image SPOT 7 [Termes IGN] image SPOT-HRS [Termes IGN] informatique en nuage [Termes IGN] Institut national de l'information géographique et forestière (France) [Termes IGN] point d'appui [Termes IGN] spatiotriangulation Résumé : (auteur) High location accuracy is a major requirement for satellite image users. Target performance is usually achieved thanks to either specific on-board satellite equipment or an auxiliary registration reference dataset. Both methods may be expensive and with certain limitations in terms of performance. The Institut national de l’information géographique et forestière (IGN) and Airbus Defence and Space (ADS) have worked together for almost 20 years, to build reference data for improving image location using multi-satellite observations. The first geometric foundation created has mainly used SPOT 5 High Resolution Stereoscopic (HRS) imagery, ancillary Ground Control Points (GCP) and Very High Resolution (VHR) imagery, providing a homogenous location accuracy of 10m CE90 almost all over the world in 2010. Space Reference Points (SRP) is a new worldwide 3D GCP database, built from a plethoric SPOT 6/7 multi-view archive, largely automatically processed, with cloud-based technologies. SRP aims at providing a systematic and reliable solution for image location (Unmanned Aerial Vehicle, VHR satellite imagery, High Altitudes Pseudo-Satellite…) and similar topics thanks to a high-density point distribution with a 3m CE90 accuracy. This paper describes the principle of SRP generation and presents the first validation results. A SPOT 6/7 smart image selection is performed to keep only relevant images for SRP purpose. The location of these SPOT 6/7 images is refined thanks to a spatiotriangulation on the worldwide geometric foundation, itself improved where needed. Points making up the future SRP database are afterward extracted thanks to classical feature detection algorithms and with respect to the expected density. Different filtering methods are applied to keep the best candidates. The last step of the processing chain is the formatting of the data to the delivery format, including metadata. An example of validation of SRP concept and specification on two tests sites (Spain and China) is then given. As a conclusion, the on-going production is shortly presented. Numéro de notice : A2020-474 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-15-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-15-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95613 [article]

CNN semantic segmentation to retrieve past land cover out of historical orthoimages and DSM: first experiments / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 1013 - 1019 Titre : CNN semantic segmentation to retrieve past land cover out of historical orthoimages and DSM: first experiments Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Sébastien Giordano , Auteur ; Clément Mallet , Auteur Année de publication : 2020 Projets : HIATUS / Giordano, Sébastien Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 1013 - 1019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] base de données historiques [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] image aérienne [Termes IGN] modèle numérique de surface [Termes IGN] occupation du sol [Termes IGN] orthoimage [Termes IGN] segmentation sémantique Résumé : (auteur) Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes occurred since the mid 20th century. They provide a relatively dense temporal sampling of the territories with a very high spatial resolution. Thus, they offer time series data which can answer a large variety of long-term environmental monitoring studies. Besides, they are generally stereoscopic surveys, making it possible to derive 3D information (Digital Surface Models). In recent years, they have often been digitized, making them more suitable to be considered in automatic analyses processes. Some photogrammetric softwares make it possible to retrieve their geometry (pose and camera calibration) and to generate corresponding DSM and orthophotomosaic. Thus, archival aerial photogrammetric surveys appear as being a powerful remote sensing data source to study land use/cover evolution over the last century. However, several difficulties have to be faced to be able to use them in automatic analysis processes. Indeed, surveys available on a study area can exhibit very different characteristics: survey pattern, focal, spatial resolution, modality (panchromatic, colour, infrared…). Planimetric and altimetric accuracies of derived products strongly depend on these characteristics. Thus, analysis processes have to cope with these uncertainties. Another important gap states in the lack of training data. Deep learning methods and especially Convolutional Neural Networks (CNN) are at present the most efficient semantic segmentation methods as long as a sufficient training dataset is available. However, temporal gaps can be very important between existing available databases and archival data. In this study, two custom variants of simple yet effective U-net - Deconv-Net inspired DL architectures are developed to process ortho-image and DSM based information. They are then trained out of a groundtruth derived out of a recent database to process archival datasets. Numéro de notice : A2020-469 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-1013-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-1013-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95637 [article]

Correction of systematic radiometric inhomogeneity in scanned aerial campaigns using principal component analysis / Lâmân Lelégard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 871 - 876 Titre : Correction of systematic radiometric inhomogeneity in scanned aerial campaigns using principal component analysis Type de document : Article/Communication Auteurs : Lâmân Lelégard , Auteur ; Arnaud Le Bris , Auteur ; Sébastien Giordano , Auteur Année de publication : 2020 Projets : HIATUS / Giordano, Sébastien Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 871 - 876 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse en composantes principales [Termes IGN] correction radiométrique [Termes IGN] homogénéisation [Termes IGN] image numérisée Résumé : (auteur) Orthophotomosaic is defined as a single image that can be layered on a map. The term “mosaic” implies that it is produced from a set of images, usually aerial images. Even if these images are taken during cloudless period, they are impaired by radiometric inhomogeneity mostly due to atmospheric phenomena, like hotspot, haze or high altitude clouds shadows as well as imaging device systematisms, like lens vignetting. These create some unsightly radiometric inhomogeneity in the orthophotomosaic that could be corrected by using a Wallis filter. Yet this solution leads to a significant loss of contrast at small scales. This work introduces an alternative to Wallis filter by considering some systematic radiometric behaviours in the images through a principal component analysis process. Numéro de notice : A2020-501 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-871-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-871-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95642 [article]

Planar polygons detection in lidar scans based on sensor topology enhanced Ransac / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 343 - 350 Titre : Planar polygons detection in lidar scans based on sensor topology enhanced Ransac Type de document : Article/Communication Auteurs : Stéphane Guinard , Auteur ; Zoumana Mallé, Auteur ; Oussama Ennafii , Auteur ; Pascal Monasse, Auteur ; Bruno Vallet , Auteur Année de publication : 2020 Projets : BIOM / Vallet, Bruno Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 343 - 350 Note générale : biblographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] polygone [Termes IGN] Ransac (algorithme) [Termes IGN] segmentation en régions [Termes IGN] semis de points [Termes IGN] topologie capteur [Termes IGN] traitement de semis de points [Termes IGN] transformation de Hough Résumé : (auteur) Detecting planar structures in point clouds is a very central step of the point cloud processing pipeline as many Lidar scans, in particular in anthropic environments, present such planar structures. Many improvements have been proposed to RANSAC and the Hough transform, the two major types of plane detection methods. An important limitation however is that these methods detect planes running across the whole scene instead of more localized planar patches. Moreover, they do not exploit the sensor information that often comes with Lidar point cloud (sensor topology and optical center position in particular). In this paper we address both issues: we aim at detecting planar polygons that have a limited spatial extent, and we exploit sensor topology. The latter is used to enhance a RANSAC framework on two aspects: to make seed points selection more local and to define more compact sets of inliers through sensor space region growing. Numéro de notice : A2020-502 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-343-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-343-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95643 [article]

Can SPOT-6/7 CNN semantic segmentation improve Sentinel-2 based land cover products? sensor assessment and fusion / Olivier Stocker in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 557 - 564 Titre : Can SPOT-6/7 CNN semantic segmentation improve Sentinel-2 based land cover products? sensor assessment and fusion Type de document : Article/Communication Auteurs : Olivier Stocker, Auteur ; Arnaud Le Bris , Auteur Année de publication : 2020 Projets : MAESTRIA / Mallet, Clément Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Projets : TOSCA Parcelle / Le Bris, Arnaud Article en page(s) : pp 557 - 564 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] fusion d'images [Termes IGN] image Sentinel-MSI [Termes IGN] image SPOT 7 [Termes IGN] occupation du sol [Termes IGN] segmentation sémantique Résumé : (auteur) Needs for fine-grained, accurate and up-to-date land cover (LC) data are important to answer both societal and scientific purposes. Several automatic products have already been proposed, but are mostly generated out of satellite sensors like Sentinel-2 (S2) or Landsat. Metric sensors, e.g. SPOT-6/7, have been less considered, while they enable (at least annual) acquisitions at country scale and can now be efficiently processed thanks to deep learning (DL) approaches. This study thus aimed at assessing whether such sensor can improve such land cover products. A custom simple yet effective U-net - Deconv-Net inspired DL architecture is developed and applied to SPOT-6/7 and S2 for different LC nomenclatures, aiming at comparing the relevance of their spatial/spectral configurations and investigating their complementarity. The proposed DL architecture is then extended to data fusion and applied to previous sensors. At the end, the proposed fusion framework is used to enrich an existing S2 based LC product, as it is generic enough to cope with fusion at distinct levels. Numéro de notice : A2020-504 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-557-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-557-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95644 [article]

Towards structureless bundle adjustment with two- and three-view structure approximation / Ewelina Rupnik in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 71 - 78 Titre : Towards structureless bundle adjustment with two- and three-view structure approximation Type de document : Article/Communication Auteurs : Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur Année de publication : 2020 Projets : 1-Pas de projet / Le Bris, Arnaud Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 71 - 78 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] approximation [Termes IGN] compensation par faisceaux [Termes IGN] estimation de pose [Termes IGN] structure-from-motion Résumé : (auteur) The global approaches solve SfM problems by independently inferring relative motions, followed be a sequential estimation of global rotations and translations. It is a fast approach but not optimal because it relies only on pairs and triplets of images and it is not a joint optimisation. In this publication we present a methodology that increases the quality of global solutions without the usual computational burden tied to the bundle adjustment. We propose an efficient structure approximation approach that relies on relative motions known upfront. Using the approximated structure, we are capable of refining the initial poses at very low computational cost. Compared to different benchmark datasets and software solutions, our approach improves the processing times while maintaining good accuracy. Numéro de notice : A2020-505 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-71-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-71-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95646 [article]