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PKS: A photogrammetric key-frame selection method for visual-inertial systems built on ORB-SLAM3 / Arash Azimi in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 191 (September 2022) . - pp 18 - 32 Titre : PKS: A photogrammetric key-frame selection method for visual-inertial systems built on ORB-SLAM3 Type de document : Article/Communication Auteurs : Arash Azimi, Auteur ; Ali Hosseininaveh Ahmadabadian, Auteur ; Fabio Remondino, Auteur Année de publication : 2022 Article en page(s) : pp 18 - 32 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie [Termes IGN] alignement [Termes IGN] cartographie et localisation simultanées [Termes IGN] centrale inertielle [Termes IGN] centre de gravité [Termes IGN] déformation d'image [Termes IGN] géoréférencement direct [Termes IGN] méthode heuristique [Termes IGN] semis de points [Termes IGN] seuillage d'image [Termes IGN] structure-from-motion [Termes IGN] vision par ordinateur Résumé : (auteur) Key-frame selection methods were developed in the past years to reduce the complexity of frame processing in visual odometry (VO) and visual simultaneous localization and mapping (VSLAM) algorithms. Key-frames help increasing algorithm's performances by sparsifying frames while maintaining its accuracy and robustness. Unlike current selection methods that rely on many heuristic thresholds to decide which key-frame should be selected, this paper proposes a photogrammetric-based key-frame selection method built upon ORB-SLAM3. The proposed algorithm, named Photogrammetric Key-frame Selection (PKS), replaces static heuristic thresholds with photogrammetric principles, ensuring algorithm’s robustness and better point cloud quality. A key-frame is chosen based on adaptive thresholds and the Equilibrium Of Center Of Gravity (ECOG) criteria as well as Inertial Measurement Unit (IMU) observations. To evaluate the proposed PKS method, the European Robotics Challenge (EuRoC) and an in-house datasets are used. Quantitative and qualitative evaluations are made by comparing trajectories, point clouds quality and completeness and Absolute Trajectory Error (ATE) in mono-inertial and stereo-inertial modes. Moreover, for the generated dense point clouds, extensive evaluations, including plane-fitting error, model deformation, model alignment error, and model density and quality, are performed. The results show that the proposed algorithm improves ORB-SLAM3 positioning accuracy by 18% in stereo-inertial mode and 20% in mono-inertial mode without the use of heuristic thresholds, as well as producing a more complete and accurate point cloud up to 50%. The open-source code of the presented method is available at https://github.com/arashazimi0032/PKS. Numéro de notice : A2022-664 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.07.003 Date de publication en ligne : 12/07/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.07.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101525 [article]

vol V-2-2022 - 2022 edition - XXIV ISPRS Congress “Imaging today, foreseeing tomorrow”, Commission II 2022 edition, 6–11 June 2022, Nice, France (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Alper Yilmaz  

Public [n° ou bulletin]  est un bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences / International society for photogrammetry and remote sensing (1980 -) (2012 - )   Titre : vol V-2-2022 - 2022 edition - XXIV ISPRS Congress “Imaging today, foreseeing tomorrow”, Commission II 2022 edition, 6–11 June 2022, Nice, France Type de document : Périodique Auteurs : Alper Yilmaz, Éditeur scientifique ; Jan Dirk Wegner, Éditeur scientifique ; Fabio Remondino, Éditeur scientifique ; et al., Auteur Année de publication : 2022 Conférence : ISPRS 2022, XXIV ISPRS Congress “Imaging today, foreseeing tomorrow”, Commission 3 06/06/2022 11/06/2022 Nice France OA ISPRS Annals Langues : Français (fre) Numéro de notice : sans Affiliation des auteurs : non IGN Nature : Numéro de périodique En ligne : https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2022/index. [...] Format de la ressource électronique : URL bulletin Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=34191 [n° ou bulletin]

Contient

• Semantic segmentation of urban textured meshes through point sampling / Grégoire Grzeczkowicz in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• Efficient dike monitoring using terrestrial SFM photogrammetry / Laurent Froideval in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• Vegetation cover mapping from RGB webcam time series for land surface emissivity retrieval in high mountain areas / Benedikt Hiebl in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• Automatic training data generation in deep learning-aided semantic segmentation of heritage buildings / Arnadi Murtiyoso in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• K-means clustering based on omnivariance attribute for building detection from airborne lidar data / Renato César Dos santos in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• Deep learning for the detection of early signs for forest damage based on satellite imagery / Dennis Wittich in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• Railway lidar semantic segmentation with axially symmetrical convolutional learning / Antoine Manier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• Effect of label noise in semantic segmentation of high resolution aerial images and height data / Arabinda Maiti in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• Learning from the past: crowd-driven active transfer learning for semantic segmentation of multi-temporal 3D point clouds / Michael Kölle in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  
• Virtual laser scanning of dynamic scenes created from real 4D topographic point cloud data / Lukas Winiwarter in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  

Exploiting light directionality for image-based 3D reconstruction of non-collaborative surfaces / Ali Karami in Photogrammetric record, vol 37 n° 177 (March 2022)  

Public [article]  inPhotogrammetric record > vol 37 n° 177 (March 2022) . - pp 111 - 138 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 points Résumé : (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 [article]

the EUROSDR time benchmark for historical aerial images / E.M. Farella (2022)  

Public Titre : the EUROSDR time benchmark for historical aerial images Type de document : Article/Communication Auteurs : E.M. Farella, Auteur ; L. Morelli, Auteur ; Fabio Remondino, Auteur ; Jon P. Mills, Auteur ; Norbert Haala, Auteur ; Joep Crompvoets, 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-B2 Conférence : ISPRS 2022, XXIV ISPRS international congress, Imaging today, foreseeing tomorrow 06/06/2022 11/06/2022 Nice France OA ISPRS Archives Importance : pp 1175 - 1182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] aérotriangulation [Termes IGN] image aérienne [Termes IGN] image ancienne [Termes IGN] image multitemporelle [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de terrain [Termes IGN] orthophotographie Mots-clés libres : benchmark Résumé : (auteur) Automatic photogrammetric processing of historical (or archival) aerial photos is still a challenging task, particularly in cases of missing ancillary information, low radiometric and image quality, limited stereo coverage or large temporal span. However, with recent advances in photogrammetry and Artificial Intelligence (AI) algorithms for image processing and interpretation, an increasing number of applications are now feasible. The article presents the TIME (hisTorical aerIal iMagEs) benchmark (https://time.fbk.eu/), promoted by EuroSDR to explore the potential of historical aerial images. Realized in collaboration with various European NMCAs, the benchmark has garnered aerial image blocks and time series imagery captured since the 1950s. To support the photogrammetric processing of the digitized photos, ancillary data are supplied with available information about flight missions, taking cameras, and ground control points (GCPs). Several diverse investigations have been undertaken with the benchmark datasets, all captured over historical urban areas or landscapes. The paper describes the benchmark datasets and some potential research topics, presenting several tests and analyses realized with the collated and shared data. Numéro de notice : C2022-021 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B2-2022-1175-2022 Date de publication en ligne : 30/05/2022 En ligne : http://dx.doi.org/10.5194/isprs-archives-XLIII-B2-2022-1175-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100847

vol V-2-2021 - July 2021 - [Actes] XXIV ISPRS Congress, Commission 2 (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Nicolas Paparoditis  

Public [n° ou bulletin]  est un bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences / International society for photogrammetry and remote sensing (1980 -) (2012 - )   Titre : vol V-2-2021 - July 2021 - [Actes] XXIV ISPRS Congress, Commission 2 Type de document : Périodique Auteurs : Nicolas Paparoditis , Éditeur scientifique ; Clément Mallet , Éditeur scientifique ; Florent Lafarge, Éditeur scientifique ; Fabio Remondino, Éditeur scientifique ; Isabella Toschi, Éditeur scientifique ; Takashi Fuse, Éditeur scientifique Année de publication : 2021 Conférence : ISPRS 2021, Commission 2, XXIV ISPRS Congress, Imaging today foreseeing tomorrow 05/07/2021 09/07/2021 Nice Virtuel France OA Annals Commission 2 Langues : Anglais (eng) Numéro de notice : sans Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Nature : Numéro de périodique nature-HAL : DirectOuvrColl/Actes En ligne : https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2021/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=33420 [n° ou bulletin]

Contient

• Fast weakly supervised detection of railway-related infrastructures in lidar acquisitions / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)  
• Towards efficient indoor/outdoor registration using planar polygons / Rahima Djahel in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)  
• Roadside tree extraction and diameter estimation with MMS lidar by using point-cloud image / Genki Takahashi in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)  
• Marrying deep learning and data fusion for accurate semantic labeling of Sentinel-2 images / Guillemette Fonteix in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)  
• Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest / Laura Alonso-Martinez in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)  

Using geometric constraints to improve performance of image classifiers for automatic segmentation of traffic signs / Roholah Yazdan in Geomatica [en ligne], vol 75 n° 1 (Mars 2021)  

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Exploiting multi-camera constraints within bundle block adjustment: an experimental comparison / Eleonora Maset (2021)  

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Towards online UAS‐based photogrammetric measurements for 3D metrology inspection / Fabio Menna in Photogrammetric record, vol 35 n° 172 (December 2020)  

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V-2 - August 2020 - [Actes] XXIV ISPRS virtual Congress, Commission 2, 31th August-2nd September 2020, Nice, France (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Nicolas Paparoditis  

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XXIV ISPRS Congress, Commission 2 / Nicolas Paparoditis (2020)  

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Workshop on Geoprocessing and Archiving of historical Aerial Images, IGN-France, Paris, June 3rd to 4th, 2019 / Clément Mallet (2019)  

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IV-2 - June 2018 - ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020", 4–7 June 2018, Riva del Garda, Italy (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Fabio Remondino

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Contextual classification using photometry and elevation data for damage detection after an earthquake event / Ewelina Rupnik in European journal of remote sensing, vol 51 n° 1 (2018)  

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A survey of geomatics solutions for the rapid mapping of natural hazards / Isabella Toschi in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 12 (December 2017)  

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Geomatics for cultural heritage preservation / Efstratios Stylianidis in GIM international [en ligne], vol 30 n° 2 (February 2016)

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