Centre de documentation
scientifique

Learning and adapting robust features for satellite image segmentation on heterogeneous data sets / Sina Ghassemi in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 9 (September 2019) . - pp 6517 - 6529 Titre : Learning and adapting robust features for satellite image segmentation on heterogeneous data sets Type de document : Article/Communication Auteurs : Sina Ghassemi, Auteur ; Attilio Friandrotti, Auteur ; Gianluca Francini, Auteur ; Enrico Magli, Auteur Année de publication : 2019 Article en page(s) : pp 6517 - 6529 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] chaîne de traitement [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] coût [Termes IGN] données hétérogènes [Termes IGN] image binaire [Termes IGN] image satellite [Termes IGN] méthode robuste [Termes IGN] réseau neuronal convolutif [Termes IGN] segmentation binaire [Termes IGN] segmentation d'image [Termes IGN] test de performance Résumé : (auteur) This paper addresses the problem of training a deep neural network for satellite image segmentation so that it can be deployed over images whose statistics differ from those used for training. For example, in postdisaster damage assessment, the tight time constraints make it impractical to train a network from scratch for each image to be segmented. We propose a convolutional encoder–decoder network able to learn visual representations of increasing semantic level as its depth increases, allowing it to generalize over a wider range of satellite images. Then, we propose two additional methods to improve the network performance over each specific image to be segmented. First, we observe that updating the batch normalization layers’ statistics over the target image improves the network performance without human intervention. Second, we show that refining a trained network over a few samples of the image boosts the network performance with minimal human intervention. We evaluate our architecture over three data sets of satellite images, showing the state-of-the-art performance in binary segmentation of previously unseen images and competitive performance with respect to more complex techniques in a multiclass segmentation task. Numéro de notice : A2019-341 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2906689 Date de publication en ligne : 17/04/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2906689 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93379 [article]

Automatic parameter selection for intensity-based registration of imagery to LiDAR data / Ebadat Ghanbari Parmehr in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7032 - 7043 Titre : Automatic parameter selection for intensity-based registration of imagery to LiDAR data Type de document : Article/Communication Auteurs : Ebadat Ghanbari Parmehr, Auteur ; Clive Simpson Fraser, Auteur ; Chunsun Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 7032 - 7043 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] appariement d'images [Termes IGN] appariement de données localisées [Termes IGN] densité de probabilité [Termes IGN] données lidar [Termes IGN] image aérienne [Termes IGN] image binaire [Termes IGN] segmentation binaire [Termes IGN] semis de points Résumé : (Auteur) Automatic registration of multisensor data, for example, imagery and Light Detection And Ranging (LiDAR), is a basic step in data fusion in the field of geospatial information processing. Mutual information (MI) has recently attracted research attention as a statistical similarity measure for intensity-based registration of multisensor images in the related fields of computer vision and remote sensing. Since MI-based registration methods rely on joint probability density functions (pdfs) for the data sets, errors in pdf estimation can affect the MI value, causing registration failure due to the presence of nonmonotonic surfaces of similarity measure. The quality of the estimated pdf is highly dependent upon both the bin size and the smoothing technique used in the pdf estimation procedure. The lack of a general approach to assign an appropriate bin size value for the pdf of multisensor data reduces both the level of automation and the robustness of the registration. In this paper, a novel bin size selection approach is proposed to improve registration reliability. The proposed method determines the best (uniform or variable) bin size for the pdf estimation via an analysis of the relationship between the similarity measure values of the data and the adopted geometric transformation. This highlights the role of the component of MI sensitive to the transformation, rather than the MI component that is unrelated to the transformation, such as noise. The performance of the proposed method for the registration of aerial imagery to LiDAR point clouds is investigated, and experimental results are compared with those achieved through a feature-based registration method. Numéro de notice : A2016-923 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2594294 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2594294 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83327 [article]

Crowd-sourced reconstruction of building interiors / Michael Peter (2016)  

Public Titre : Crowd-sourced reconstruction of building interiors Type de document : Thèse/HDR Auteurs : Michael Peter, Auteur ; Dieter Fritsch, Directeur de thèse Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2016 Collection : DGK - C, ISSN 0065-5325 num. 768 Importance : 147 p. ISBN/ISSN/EAN : 978-3-7696-5180-5 Note générale : bibliographie Langues : Anglais (eng) Allemand (ger) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] carte d'intérieur [Termes IGN] cartographie collaborative [Termes IGN] données localisées des bénévoles [Termes IGN] échelle cartographique [Termes IGN] image binaire [Termes IGN] modélisation 2D [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] navigation à l'estime [Termes IGN] numérisation de carte [Termes IGN] plan incendie [Termes IGN] positionnement en intérieur [Termes IGN] segmentation binaire [Termes IGN] squelettisation [Termes IGN] trace GPS Résumé : (auteur) Location-based services (LBS) have gained huge commercial and scientific interest in recent years, due to the ubiquitous and free availability of maps, global positioning systems, and smartphones. To date, maps and positioning solutions are mostly only available for outdoor use. However, humans spend most of their time indoors, rendering indoor LBS interesting for applications such as location-based advertisement, customer tracking and customer flow analysis. Neither of the two prerequisites for indoor LBS - a map of the user's environment and a positioning system - is currently generally available: Most positioning methods currently under scientific investigation are based either on fingerprint maps of electro-magnetic signals (e.g. WiFi) or inertial measurement units. To overcome the flaws of these methods, they are often supported by models for the human movement which in turn rely on indoor maps. Ready-made maps, on the other hand, are generally unavailable due to indoor mapping being mostly manual, expensive and tedious. The vast amount of unmapped indoor space therefore calls for the transfer of methods used by Volunteered Geographic Information (VGI) communities like OpenStreetMap to indoor mapping. These methods comprise the digitization of features of interest such as building outlines from aerial images released to the community and the use of position traces. In this thesis, approaches are illustrated which can serve to enable this transfer. On the one hand, the thesis shows how photographs of evacuation plans - which are a compulsory part of the safety equipment of publicly used buildings in many countries - can substitute for the aerial images in the indoor domain. Due to the standardised nature of such plans, the manual digitization employed by VGI mappers in the outdoor domain can be replaced by an automatic reverse-engineering pipeline. To this end, the image is pre-processed and symbols, which depict evacuation routes or emergency equipment, are detected. Subsequently, foreground objects (i.e. walls) are distinguished from the background using an adequate binarisation operation. Based on the binary image, the sought-after vector information can be extracted by skeletonisation and skeleton tracing. The model is finalised by a bridging operation of the previously detected symbols which occlude parts of walls or stairs. As the model resulting from these operations is only available in a coordinate system defined by the original image, the transformation to a world-coordinate system or, at least, the unknown scale has to be determined. To this end, the indoor model is matched to an available model of the building's external shell. By detection of stairs, an approximate floor height can be computed and the 2D model is extruded to a 3D model. On the other hand, geometric features and semantic annotations may be added to existing models using pedestrian traces recorded by an indoor positioning system. As suitable generally available and low-cost systems do not exist yet, their existence is simulated in this work by a dead-reckoning system basing on a foot-mounted inertial measurement system. Methods for the derivation of the initial position and orientation necessary for the application of such a system are shown, as well as methods enabling the correction of remaining errors. The latter comprise an alignment approach using the external building shell and a map-matching method which employs the existing coarse model derived from the evacuation plan. Building on the collected pedestrian traces, semi-automatic and automatic approaches for the existing models' semantic and geometric refinement are presented which range from semantic annotation using the analysis of photographed doorplates to automatic door reconstruction. Furthermore, a geometric update of single rooms by conjoint analysis of the coarse model, pedestrian traces and a hand-held low-cost range camera is described. Lastly, works of indoor mapping are presented which are based on pedestrian traces and higher-level knowledge about the interior structure of the building modelled in an indoor grammar. Due to the differing characteristics of the two central elements of building interiors, corridors and rooms, the grammar is composed of a Lindenmayer system modelling the floor's corridor system and a split grammar describing the room layout which is found in the non-corridor spaces. The grammar is put to the test by applying it to distributedly collected noisy trace data. Numéro de notice : 19790 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Thèse étrangère Note de thèse : PhD Dissertation : Photogrammetry : Stuttgart : 2016 nature-HAL : Thèse DOI : 10.18419/opus-8729 En ligne : http://doi.org/10.18419/opus-8729 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85009

3D octree based watertight mesh generation from ubiquitous data / Laurent Caraffa (2015)  

Public contenu dans ISPRS Geospatial Week 2015 / Clément Mallet (2015)   Titre : 3D octree based watertight mesh generation from ubiquitous data Type de document : Article/Communication Auteurs : Laurent Caraffa , Auteur ; Mathieu Brédif , Auteur ; Bruno Vallet , Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2015 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 40-3/W3 Conférence : ISPRS 2015, Geospatial Week : Laserscanning, ISSDQ, CMRT, ISA, GeoVIS, GeoBigData 28/09/2015 03/10/2015 La Grande Motte France ISPRS OA Archives Importance : pp 613 - 617 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme Graph-Cut [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] maillage par triangles [Termes IGN] octree [Termes IGN] reconstruction d'objet [Termes IGN] segmentation binaire Résumé : (auteur) Despite of the popularity of Delauney structure for mesh generation, octree based approaches remain an interesting solution for a first step surface reconstruction. In this paper, we propose a generic framework for a octree cell based mesh generation. Its input is a set of Lidar-based 3D measurements or other inputs which are formulated as a set of mass functions that characterize the level of confidence on the occupancy of each octree’s leaf. The output is a binary segmentation of the space between occupied and empty areas by taking into account the uncertainty of data. To this end, the problem is then reduced to a global energy optimization framework efficiently optimized with a min-cut approach. We use the approach for producing a large scale surface reconstruction algorithm by merging data from ubiquitous sources like airborne, terrestrial Lidar data, occupancy map and extra cues. Once the surface is computed, a solution is proposed for texturing the mesh. Numéro de notice : C2015-005 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/MATHEMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprsarchives-XL-3-W3-613-2015 Date de publication en ligne : 19/08/2015 En ligne : http://dx.doi.org/10.5194/isprsarchives-XL-3-W3-613-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80295

Independent two-step thresholding of binary images in inter-annual land cover change/no-change identification / Priyakant Sinha in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 81 (July 2013) . - pp 31 - 43 Titre : Independent two-step thresholding of binary images in inter-annual land cover change/no-change identification Type de document : Article/Communication Auteurs : Priyakant Sinha, Auteur ; Lalit Kumar, Auteur Année de publication : 2013 Article en page(s) : pp 31 - 43 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] analyse diachronique [Termes IGN] détection de changement [Termes IGN] écart type [Termes IGN] image binaire [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] occupation du sol [Termes IGN] segmentation binaire [Termes IGN] seuillage d'image Résumé : (Auteur) Binary images from one or more spectral bands have been used in many studies for land-cover change/no-change identification in diverse climatic conditions. Determination of appropriate threshold levels for change/no-change identification is a critical factor that influences change detection result accuracy. The most used method to determine the threshold values is based on the standard deviation (SD) from the mean, assuming the amount of change (due to increase or decrease in brightness values) to be symmetrically distributed on a standard normal curve, which is not always true. Considering the asymmetrical nature of distribution histogram for the two sides, this study proposes a relatively simple and easy ‘Independent Two-Step’ thresholding approach for optimal threshold value determination for spectrally increased and decreased part using Normalized Difference Vegetation Index (NDVI) difference image. Six NDVI differencing images from 2007 to 2009 of different seasons were tested for inter-annual or seasonal land cover change/no-change identification. The relative performances of the proposed and two other methods towards the sensitivity of distributions were tested and an improvement of ~3% in overall accuracy and of ~0.04 in Kappa was attained with the Proposed Method. This study demonstrated the importance of consideration of normality of data distributions in land-cover change/no-change analysis. Numéro de notice : A2013-387 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.03.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.03.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32525 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2013071	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Recalage d'un nuage de points de scanner laser terrestre avec une image de bâtiment / Abdelhamid Bennis (2011)  

Permalink

La morphologie mathématique binaire pour l'extraction automatique des bâtiments dans les images THRS / David Sheeren in Revue internationale de géomatique, vol 17 n° 3-4 (septembre 2007 – février 2008)  

Permalink

Traitement et analyse des images numériques / S. Bres (2003)

Permalink

Recherche automatique des réseaux linéaires sur les images SPOT / D. Destival in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 105 (Janvier 1987)

Permalink