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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)
[article]
Titre : Learning from the past: crowd-driven active transfer learning for semantic segmentation of multi-temporal 3D point clouds Type de document : Article/Communication Auteurs : Michael Kölle, Auteur ; Volker Walter, Auteur ; Uwe Soergel, Auteur Année de publication : 2022 Article en page(s) : pp 259 - 266 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données étiquetées d'entrainement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] données multitemporelles
[Termes IGN] orthoimage couleur
[Termes IGN] production participative
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] traitement de données localiséesRésumé : (auteur) The main bottleneck of machine learning systems, such as convolutional neural networks, is the availability of labeled training data. Hence, much effort (and thus cost) is caused by setting up proper training data sets. However, models trained on specific data sets often perform unsatisfactorily when used to derive predictions for another (yet related) data set. We aim to overcome this problem by employing active learning to iteratively adapt an existing classifier to another domain. Precisely, we are concerned with semantic segmentation of 3D point clouds of multiple epochs. We first establish a Random Forest classifier for the first epoch of our data set and adapt it for successful prediction to two more temporally disjoint point clouds of the same but extended area. The point clouds, which are part of the newly introduced Hessigheim 3D benchmark data set, incorporate different characteristics with respect to the acquisition date and sensor configuration. We demonstrate that our workflow for domain adaptation is designed in such a way that it i) offers the possibility to greatly reduce labeling effort compared to a passive learning baseline or to an active learning baseline trained from scratch, if the domain gap is small enough and ii) at least does not cause more expenses (compared to a newly initialized active learning loop), if the domain gap is severe. The latter is especially beneficial in scenarios where the similarity of two different domains is hard to assess. Numéro de notice : A2022-435 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-2-2022-259-2022 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2022-259-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100743
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2022 (2022 edition) . - pp 259 - 266[article]
Titre : Advances in SAR: Sensors, Methodologies, and Applications Type de document : Monographie Auteurs : Timo Balz, Éditeur scientifique ; Uwe Soergel, Éditeur scientifique ; Mattia Crespi, Éditeur scientifique ; Batuhan Osmanoglu, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2018 Importance : 530 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-3-03897-183-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] étalonnage
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] image TanDEM-X
[Termes IGN] image TerraSAR-X
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] polarimétrie radar
[Termes IGN] télédétection en hyperfréquenceRésumé : (éditeur) The key importance of radar remote sensing for civil applications has been recognized for decades, and enormous scientific and technical developments have been carried out to further improve SAR sensors and SAR data processing. In recent years, SAR satellite constellations, consisting of two or more satellites, are becoming the “new normal” in SAR remote sensing. The present availability of SAR sensor constellations, such as Cosmo SkyMed, TerraSAR-X/TanDEM-X, and the new Copernicus sensors Sentinel-1A and 1B, supply a continuous stream of imagery with a unique short revisit cycle of only six days. Together with many more operational and planned SAR satellite systems, such as Geo-Fen 3 or NASA ISRO SAR (NISAR), this unprecedented amount of high-quality SAR data is suitable for a variety of applications, provided proper data processing methodology are applied. In "Advances in SAR: Sensors, Methodologies, and Applications" advancements in the field of hardware, software, and applications are presented, covering a wide range of topics. Note de contenu : 1- Pre-flight SAOCOM-1A SAR performance assessment by outdoor campaign
2- On the design of radar corner reflectors for deformation monitoring in
multi-frequency InSAR
3- Identification of C-Band radio frequency interferences from Sentinel-1 data
4- An accelerated backprojection algorithm for monostatic and bistatic SAR processing
5- Signal processing for a multiple-input,division frequency-modulated continuous wave (FMCW)
6- Fast and efficient correction of ground moving targets in a Synthetic Aperture Radar, single-look complex image
7- A unified algorithm for channel imbalance and antenna phase center position calibration of a single-pass multi-baseline TomoSAR System
8- InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by
New Advances
9- Modeling orbital error in InSAR interferogram using frequency and spatial domain
based methods
10- Ionospheric reconstructions using Faraday rotation in spaceborne polarimetric SAR data
11- An efficient maximum likelihood estimation approach of multi-baseline SAR interferometry for refined topographic mapping in mountainous areas
12- Elevation extraction and deformation monitoring by multitemporal InSAR of Lupu Bridge in Shanghai
13- Ground deformations around the Toktogul reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 data - A case study about the impact of atmospheric corrections on InSAR
time series
14- Time series analysis of very slow landslides in the Three Gorges region through small baseline SAR offset tracking
15- Landslide displacement monitoring with split- bandwidth interferometry: A case study of the shuping landslide in the Three Gorges area
16- Split-band interferometry-assisted phase unwrapping for the phase ambiguities correction
17- Better estimated IEM input parameters using random fractal geometry applied on
multi-frequency SAR data
18- The role of resolution in the estimation of fractal dimension maps From SAR data
19- Statistical modeling of polarimetric SAR data: A survey and challenges
20- Multi-feature segmentation for high-resolution polarimetric SAR data based on fractal net evolution approach
21- PolSAR land cover classification based on roll-invariant and selected hidden polarimetric features in the rotation domain
22- A SAR-based index for landscape changes in African savannas
23- Semi-automated surface water detection with Synthetic Aperture Radar Data: A wetland case study
24- Coherence change-detection with Sentinel-1 for natural and anthropogenic disaster
monitoring in urban areas
25- Multi-layer model based on multi-scale and multi-feature fusion for SAR images
26- L-Band temporal coherence assessment and modeling using amplitude and snow depth
over interior AlaskaNuméro de notice : 28510 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03897-183-2 En ligne : https://doi.org/10.3390/books978-3-03897-183-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97066 vol III-7 - July 2016 - [actes] XXIII ISPRS Congress, Commission 7, 12–19 July 2016, Prague, Czech Republic (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Lena Halounova
[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 III-7 - July 2016 - [actes] XXIII ISPRS Congress, Commission 7, 12–19 July 2016, Prague, Czech Republic Type de document : Périodique Auteurs : Lena Halounova, Éditeur scientifique ; F. Sunar, Éditeur scientifique ; Markéta Potůčková, Éditeur scientifique ; L. Patková, Éditeur scientifique ; M. Yoshimura, Éditeur scientifique ; Uwe Soergel, Éditeur scientifique ; Eyal Ben-Dor, Éditeur scientifique ; J. Smit, Éditeur scientifique ; G. Bareth, Éditeur scientifique ; J. Zhang, Éditeur scientifique ; S. Kaasalainen, Éditeur scientifique ; Batuhan Osmanoglu, Éditeur scientifique ; M. Crespi, Éditeur scientifique ; Michele Crosetto, Éditeur scientifique ; Thomas Blaschke, Éditeur scientifique ; Maria Antonia Brovelli, Éditeur scientifique ; B. Zagajewski, Éditeur scientifique Congrès : ISPRS 2016, 23th international congress (12 - 19 juillet 2016; Prague, République tchèque), Auteur Année de publication : 2016 Langues : Français (fre) Numéro de notice : sans Affiliation des auteurs : non IGN Nature : Numéro de périodique En ligne : http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-7/index.html Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=27508 [n° ou bulletin]vol 100 - February 2015 - High-resolution Earth imaging for geospatial information (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / Christian Heipke
[n° ou bulletin]
est un bulletin de ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1980 -) (1990 -)
Titre : vol 100 - February 2015 - High-resolution Earth imaging for geospatial information Type de document : Périodique Auteurs : Christian Heipke, Éditeur scientifique ; Uwe Soergel, Éditeur scientifique ; Franz Rottensteiner, Éditeur scientifique ; Boris Jutzi, Éditeur scientifique Année de publication : 2015 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] façade
[Termes IGN] image hyperspectrale
[Termes IGN] MicMac
[Termes IGN] réseau de surveillance géophysiqueNuméro de notice : 081-201502 Affiliation des auteurs : non IGN Nature : Numéro de périodique En ligne : http://www.sciencedirect.com/science/journal/09242716/100 Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=24835 [n° ou bulletin]Contient
- In-flight photogrammetric camera calibration and validation via complementary lidar / A.S. Gneeniss in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)
- Coregistration refinement of hyperspectral images and DSM: An object-based approach using spectral information / Janja Avbelj in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)
- Radiometric and geometric evaluation of GeoEye-1, WorldView-2 and Pléiades-1A stereo images for 3D information extraction / Daniela Poli in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)
- Measurement of ground displacement from optical satellite image correlation using the free open-source software MicMac / Ana-Maria Rosu in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)
- Evaluation and comparison of different radargrammetric approaches for Digital Surface Models generation from COSMO-SkyMed, TerraSAR-X, RADARSAT-2 imagery: Analysis of Beauport (Canada) test site / P. Capaldo in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)
- Measuring thermal expansion using X-band persistent scatterer interferometry / Michele Crosetto in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)
- Persistent scatterers at building facades – Evaluation of appearance and localization accuracy / Stefan Gernhardt in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)
- Integrating SAR and derived products into operational volcano monitoring and decision support systems / Franz J. Meyer in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)
Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2015021 RAB Revue Centre de documentation En réserve L003 Disponible Contextual classification of lidar data and building object detection in urban areas / Joachim Niemeyer in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Contextual classification of lidar data and building object detection in urban areas Type de document : Article/Communication Auteurs : Joachim Niemeyer, Auteur ; Franz Rottensteiner, Auteur ; Uwe Soergel, Auteur Année de publication : 2014 Article en page(s) : pp 152 - 165 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification contextuelle
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] milieu urbain
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] semis de pointsRésumé : (Auteur) In this work we address the task of the contextual classification of an airborne LiDAR point cloud. For that purpose, we integrate a Random Forest classifier into a Conditional Random Field (CRF) framework. It is a flexible approach for obtaining a reliable classification result even in complex urban scenes. In this way, we benefit from the consideration of context on the one hand and from the opportunity to use a large amount of features on the other hand. Considering the interactions in our experiments increases the overall accuracy by 2%, though a larger improvement becomes apparent in the completeness and correctness of some of the seven classes discerned in our experiments. We compare the Random Forest approach to linear models for the computation of unary and pairwise potentials of the CRF, and investigate the relevance of different features for the LiDAR points as well as for the interaction of neighbouring points. In a second step, building objects are detected based on the classified point cloud. For that purpose, the CRF probabilities for the classes are plugged into a Markov Random Field as unary potentials, in which the pairwise potentials are based on a Potts model. The 2D binary building object masks are extracted and evaluated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction. The evaluation shows that the main buildings (larger than 50 m2) can be detected very reliably with a correctness larger than 96% and a completeness of 100%. Numéro de notice : A2014-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32922
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 152 - 165[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Grouping of Persistent Scatterers in high-resolution SAR data of urban scenes / A. Schunert in ISPRS Journal of photogrammetry and remote sensing, vol 73 (September 2012)PermalinkRelevance assessment of full-waveform lidar data for urban area classification / Clément Mallet in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 6 supplement (December 2011)PermalinkPermalinkConditional random fields for urban scene : Classification with full waveform LiDAR Data / Joachim Niemeyer (2011)PermalinkA marked point process for modeling lidar waveforms / Clément Mallet in IEEE Transactions on image processing, vol 19 n° 12 (December 2010)PermalinkPermalinkStereo analysis of high-resolution SAR images for building height estimation in cases of orthogonal aspect directions / Uwe Soergel in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 5 (September - October 2009)PermalinkPermalinkAnalysis of full-waveform lidar data for classification of urban areas / Clément Mallet in Photogrammetrie Fernerkundung Geoinformation, vol 2008 n° 5 ([01/09/2008])PermalinkPermalink