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GOTMI / Papadakis, Nicolas
Nom :
GOTMI
titre complet :
Generalized Optimal Transport Models for Image processing
Auteurs :
Papadakis, Nicolas
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Titre : Visibility estimation in point clouds with variable density Type de document : Article/Communication Auteurs : Pierre Biasutti , Auteur ; Aurélie Bugeau, Auteur ; Jean-François Aujol, Auteur ; Mathieu Brédif , Auteur Editeur : Setúbal [Portugal] : Science and Technology Publications - Scitepress Année de publication : 2019 Projets : GOTMI / Papadakis, Nicolas Conférence : VISAPP 2019, 14th International Conference on Computer Vision Theory and Applications 25/02/2019 25/02/2019 Prague République tchèque https://www.scitepress.org/ProceedingsDetails.aspx?ID=IBjeE0qpff8=&t=1 Importance : pp 27 - 35 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] visibilité
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) Estimating visibility in point clouds has many applications such as visualization, surface reconstruction and scene analysis through fusion of LiDAR point clouds and images. However, most current works rely on methods that require strong assumptions on the point cloud density, which are not valid for LiDAR point clouds acquired from mobile mapping systems, leading to low quality of point visibility estimations. This work presents a novel approach for the estimation of the visibility of a point cloud from a viewpoint. The method is designed to be fully automatic and it makes no assumption on the point cloud density. The visibility of each point is estimated by considering its screen-space neighborhood from the given viewpoint. Our results show that our approach succeeds better in estimating the visibility on real-world data acquired using LiDAR scanners. We evaluate our approach by comparing its results to a new manually annotated dataset, which we make available online. Numéro de notice : C2019-007 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : URL preprint Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5220/0007308600270035 En ligne : http://dx.doi.org/10.5220/0007308600270035 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92633 Documents numériques
en open access
Visibility estimation in point clouds with variable density - version HALURL Range-image: Incorporating sensor topology for lidar point cloud processing / Pierre Biasutti in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)
[article]
Titre : Range-image: Incorporating sensor topology for lidar point cloud processing Type de document : Article/Communication Auteurs : Pierre Biasutti , Auteur ; Jean-François Aujol, Auteur ; Mathieu Brédif , Auteur ; Aurélie Bugeau, Auteur Année de publication : 2018 Projets : GOTMI / Papadakis, Nicolas Article en page(s) : pp 367 - 375 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de partie cachée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] histogramme
[Termes IGN] image 2D
[Termes IGN] objet mobile
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] topologie capteurRésumé : (auteur) This paper proposes a novel methodology for lidar point cloud processing that takes advantage of the implicit topology of various lidar sensors to derive 2D images from the point cloud while bringing spatial structure to each point. The interest of such a methodology is then proved by addressing the problems of segmentation and disocclusion of mobile objects in 3D lidar scenes acquired using street-based Mobile Mapping Systems (MMS). Most of the existing lines of research tackle those problems directly in the 3D space. This work promotes an alternative approach by using this image representation of the 3D point cloud, taking advantage of the fact that the problem of disocclusion has been intensively studied in the 2D image processing community over the past decade. Using the image derived from the sensor data by exploiting the sensor topology, a semi-automatic segmentation procedure based on depth histograms is presented. Then, a variational image inpainting technique is introduced to reconstruct the areas that are occluded by objects. Experiments and validation on real data prove the effectiveness of this methodology both in terms of accuracy and speed. Numéro de notice : A2018-230 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.6.367 Date de publication en ligne : 01/06/2018 En ligne : https://doi.org/10.14358/PERS.84.6.367 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90171
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 6 (juin 2018) . - pp 367 - 375[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2018061 RAB Revue Centre de documentation En réserve L003 Disponible Documents numériques
en open access
Range-image: Incorporating sensor topology - version HALAdobe Acrobat PDF Disocclusion of 3D LiDAR point clouds using range images / Pierre Biasutti in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-1/W1 (May 2017)
[article]
Titre : Disocclusion of 3D LiDAR point clouds using range images Type de document : Article/Communication Auteurs : Pierre Biasutti , Auteur ; Jean-François Aujol, Auteur ; Mathieu Brédif , Auteur ; Aurélie Bugeau, Auteur Année de publication : 2017 Projets : GOTMI / Papadakis, Nicolas Conférence : ISPRS 2017, Workshops HRIGI – CMRT – ISA – EuroCOW 06/06/2017 09/06/2017 Hanovre Allemagne ISPRS OA Annals Article en page(s) : pp 75 - 82 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] objet mobile
[Termes IGN] retouche
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsRésumé : (auteur) This paper proposes a novel framework for the disocclusion of mobile objects in 3D LiDAR scenes aquired via street-based Mobile Mapping Systems (MMS). Most of the existing lines of research tackle this problem directly in the 3D space. This work promotes an alternative approach by using a 2D range image representation of the 3D point cloud, taking advantage of the fact that the problem of disocclusion has been intensively studied in the 2D image processing community over the past decade. First, the point cloud is turned into a 2D range image by exploiting the sensor’s topology. Using the range image, a semi-automatic segmentation procedure based on depth histograms is performed in order to select the occluding object to be removed. A variational image inpainting technique is then used to reconstruct the area occluded by that object. Finally, the range image is unprojected as a 3D point cloud. Experiments on real data prove the effectiveness of this procedure both in terms of accuracy and speed. Numéro de notice : A2017-898 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-IV-1-W1-75-2017 Date de publication en ligne : 30/05/2017 En ligne : https://doi.org/10.5194/isprs-annals-IV-1-W1-75-2017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91913
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-1/W1 (May 2017) . - pp 75 - 82[article]