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Affiner la recherche Interroger des sources externesImproving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours / David Griffiths in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
Titre : Improving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours Type de document : Article/Communication Auteurs : David Griffiths, Auteur ; Jan Boehm, Auteur Année de publication : 2019 Article en page(s) : pp 70 - 83 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes descripteurs IGN] apprentissage profond
[Termes descripteurs IGN] bati
[Termes descripteurs IGN] classification par réseau neuronal convolutif
[Termes descripteurs IGN] détection de contours
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] données localisées 3D
[Termes descripteurs IGN] données publiques
[Termes descripteurs IGN] fusion de données
[Termes descripteurs IGN] image RVB
[Termes descripteurs IGN] Royaume-Uni
[Termes descripteurs IGN] scène urbaine
[Termes descripteurs IGN] segmentation sémantique
[Termes descripteurs IGN] zone ruraleRésumé : (Auteur) Robust and reliable automatic building detection and segmentation from aerial images/point clouds has been a prominent field of research in remote sensing, computer vision and point cloud processing for a number of decades. One of the largest issues associated with deep learning methods is the high quantity of data required for training. To help address this we present a method to improve public GIS building footprint labels by using Morphological Geodesic Active Contours (MorphGACs). We demonstrate by improving the quality of building footprint labels for detection and semantic segmentation, more robust and reliable models can be obtained. We evaluate these methods over a large UK-based dataset of 24556 images containing 169835 building instances. This is achieved by training several Mask/Faster R-CNN and RetinaNet deep convolutional neural networks. Networks are supplied with both RGB and fused RGB-lidar data. We offer quantitative analysis on the benefits of the inclusion of depth data for building segmentation. By employing both methods we achieve a detection accuracy of 0.92 (mAP@0.5) and segmentation f1 scores of 0.94 over a 4911 test images ranging from urban to rural scenes. Numéro de notice : A2019-265 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.013 date de publication en ligne : 06/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.013 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93079
in ISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 70 - 83[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019081 SL Revue Centre de documentation Revues en salle Disponible 081-2019083 DEP-RECP Revue MATIS Dépôt en unité Exclu du prêt 081-2019082 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt 
Titre : The iQmulus urban showcase: automatic tree classification and identification in huge mobile mapping point clouds Type de document : Article/Communication Auteurs : Jan Boehm, Auteur ; Mathieu Brédif Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2016 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. XLI-B3 Projets : IQmulus / Brédif, Mathieu Importance : pp 301 - 307 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes descripteurs IGN] analyse en composantes principales
[Termes descripteurs IGN] arbre urbain
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] données localisées 3D
[Termes descripteurs IGN] données massives
[Termes descripteurs IGN] Spark
[Termes descripteurs IGN] Toulouse
[Termes descripteurs IGN] traitement de données localiséesRésumé : (auteur) Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study, the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow. Numéro de notice : C2016-041 Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLI-B3-301-2016 date de publication en ligne : 09/06/2016 En ligne : https://doi.org/10.5194/isprs-archives-XLI-B3-301-2016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91853 Documents numériques
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Titre : Stereo-imaging network design for precise and dense 3D reconstruction Type de document : Article/Communication Auteurs : Ali Hosseininaveh Ahmadabadian, Auteur ; S. Robson, Auteur ; Jan Boehm, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 317 - 336 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes descripteurs IGN] angle de visée
[Termes descripteurs IGN] modèle stéréoscopique
[Termes descripteurs IGN] photogrammétrie terrestre
[Termes descripteurs IGN] reconstruction 3D
[Termes descripteurs IGN] système de référence localRésumé : (Auteur) This paper presents a novel stereo-imaging network design strategy comprising four steps: datum definition, optimum distance estimation, candidate camera position generation, and lastly clustering and selection of vantage viewpoints. An approximate 3D mesh model of an object from a quick low-cost system is used in the first step of the method. An ellipsoid is fitted to the rough model in order to find a suitable imaging distance regarding range- and visibility-related constraints for a stereopair. Next, a set of viewpoints is provided taking into account the ellipsoid and the calculated distance. Finally, camera positions and orientations are defined by clustering and choosing the vantage viewpoints. A system, called “imaging network designer” (IND), has been developed based on this method and is evaluated with two different tests. Results show that IND can provide an imaging network, which fulfils the expected precision for the entire object. Numéro de notice : A2014-491 Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74080
in Photogrammetric record > vol 29 n° 147 (September - November 2014) . - pp 317 - 336[article]Réservation
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Titre : A comparison of dense matching algorithms for scaled surface reconstruction using stereo camera rigs Type de document : Article/Communication Auteurs : Ali Hosseininaveh Ahmadabadian, Auteur ; Stuart Robson, Auteur ; Jan Boehm, Auteur Année de publication : 2013 Article en page(s) : pp 157 - 167 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] analyse comparative
[Termes descripteurs IGN] appariement d'images
[Termes descripteurs IGN] chambre de prise de vue numérique
[Termes descripteurs IGN] compensation par faisceaux
[Termes descripteurs IGN] contrainte géométrique
[Termes descripteurs IGN] échelle
[Termes descripteurs IGN] espace objet
[Termes descripteurs IGN] instrumentation Nikon
[Termes descripteurs IGN] MicMac
[Termes descripteurs IGN] précision stéréoscopique
[Termes descripteurs IGN] reconstruction 3D
[Termes descripteurs IGN] reconstruction d'objet
[Termes descripteurs IGN] semis de pointsRésumé : (Auteur) Photogrammetric methods for dense 3D surface reconstruction are increasingly available to both professional and amateur users who have requirements that span a wide variety of applications. One of the key concerns in choosing an appropriate method is to understand the achievable accuracy and how choices made within the workflow can alter that outcome. In this paper we consider accuracy in two components: the ability to generate a correctly scaled 3D model; and the ability to automatically deliver a high quality data set that provides good agreement to a reference surface. The determination of scale information is particularly important, since a network of images usually only provides angle measurements and thus leads to unscaled geometry. A solution is the introduction of known distances in object space, such as base lines between camera stations or distances between control points. In order to avoid using known object distances, the method presented in this paper exploits a calibrated stereo camera utilizing the calibrated base line information from the camera pair as an observational based geometric constraint. The method provides distance information throughout the object volume by orbiting the object. In order to test the performance of this approach, four topical surface matching methods have been investigated to determine their ability to produce accurate, dense point clouds. The methods include two versions of Semi-Global Matching as well as MicMac and Patch-based Multi-View Stereo (PMVS). These methods are implemented on a set of stereo images captured from four carefully selected objects by using (1) an off-the-shelf low cost 3D camera and (2) a pair of Nikon D700 DSLR cameras rigidly mounted in close proximity to each other. Inter-comparisons demonstrate the subtle differences between each of these permutations. The point clouds are also compared to a dataset obtained with a Nikon MMD laser scanner. Finally, the established process of achieving accurate point clouds from images and known object space distances are compared with the presented strategies. Results from the matching demonstrate that if a good imaging network is provided, using a stereo camera and bundle adjustment with geometric constraints can effectively resolve the scale. Among the strategies for dense 3D reconstruction, using the presented method for solving the scale problem and PMVS on the images captured with two DSLR cameras resulted in a dense point cloud as accurate as the Nikon laser scanner dataset. Numéro de notice : A2013-184 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32322
in ISPRS Journal of photogrammetry and remote sensing > vol 78 (April 2013) . - pp 157 - 167[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013041 RAB Revue Centre de documentation En réserve 3L Disponible vol 76 - February 2013 - Special issue: Terrestrial 3D modelling (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / International society for photogrammetry and remote sensing
est un bulletin de ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1990 - )
Titre : vol 76 - February 2013 - Special issue: Terrestrial 3D modelling Type de document : Périodique Auteurs : International society for photogrammetry and remote sensing, Auteur ; Fabio Remondino, Editeur scientifique ; Jan Boehm, Editeur scientifique Année de publication : 2013 Importance : 102 p. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie Numéro de notice : 081-201302 Thématique : IMAGERIE Nature : Numéro de périodique En ligne : http://www.sciencedirect.com/science/journal/09242716/76 Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=17311 [n° ou bulletin]Contient
- Model driven reconstruction of roofs from sparse LIDAR point clouds / A. Henn in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
- Segmentation of terrestrial laser scanning data using geometry and image information / S. Barnea in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
- Combining terrestrial stereophotogrammetry, DGPS and GIS-based 3D voxel modelling in the volumetric recording of archaeological features / H. Orengo in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
- Ground filtering and vegetation mapping using multi-return terrestrial laser scanning / F. Pirotti in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
- Automatic orientation and 3D modelling from markerless rock art imagery / J. Lerma in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
- One billion points in the cloud – an octree for efficient processing of 3D laser scans / Jan Elseberg in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
- Historic building information modelling – Adding intelligence to laser and image based surveys of European classical architecture / H. Murphy in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
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