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Piecewise-planar approximation of large 3D data as graph-structured optimization / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2/W5 (may 2019)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-2/W5 (may 2019) . - pp 365 - 372 Titre : Piecewise-planar approximation of large 3D data as graph-structured optimization Type de document : Article/Communication Auteurs : Stéphane Guinard , Auteur ; Loïc Landrieu , Auteur ; Laurent Caraffa , Auteur ; Bruno Vallet , Auteur Congrès : ISPRS Geospatial Week 2019 (10 - 14 juin 2019; Enschede, Pays-Bas), Commanditaire Année de publication : 2019 Article en page(s) : pp 365 - 372 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] algorithme de décalage moyen [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] approximation [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] érosion anthropique [Termes descripteurs IGN] erreur d'approximation [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] graphe [Termes descripteurs IGN] maillage [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] surface plane Résumé : (auteur) We introduce a new method for the piecewise-planar approximation of 3D data, including point clouds and meshes. Our method is designed to operate on large datasets (e.g. millions of vertices) containing planar structures, which are very frequent in anthropic scenes. Our approach is also adaptive to the local geometric complexity of the input data. Our main contribution is the formulation of the piecewise-planar approximation problem as a non-convex optimization problem. In turn, this problem can be efficiently solved with a graph-structured working set approach. We compare our results with a state-of-the-art region-growing-based segmentation method and show a significant improvement both in terms of approximation error and computation efficiency. Numéro de notice : A2019-592 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-IV-2-W5-365-2019 date de publication en ligne : 29/05/2019 En ligne : https://doi.org/10.5194/isprs-annals-IV-2-W5-365-2019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94552 [article]

3D watertight mesh generation with uncertainties from ubiquitous data / Laurent Caraffa (2016)  

Public Titre : 3D watertight mesh generation with uncertainties from ubiquitous data Type de document : Article/Communication Auteurs : Laurent Caraffa , Auteur ; Mathieu Brédif , Auteur ; Bruno Vallet , Auteur Congrès : ACCV 2016, 13th Asian Conference on Computer Vision (20 - 24 novembre 2016; Taipei, Taiwan), Commanditaire Editeur : Springer International Publishing Année de publication : 2016 Collection : Lecture Notes in Computer Science num. 10114 Projets : IQmulus / Brédif, Mathieu Importance : pp 377 - 391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] algorithme Graph-Cut [Termes descripteurs IGN] carte de confiance [Termes descripteurs IGN] distance de Hausdorff [Termes descripteurs IGN] incertitude géométrique [Termes descripteurs IGN] maille triangulaire [Termes descripteurs IGN] reconstruction d'objet [Termes descripteurs IGN] seuillage [Termes descripteurs IGN] surface imperméable [Termes descripteurs IGN] théorie de Dempster-Shafer Résumé : (auteur) In this paper, we propose a generic framework for watertight mesh generation with uncertainties that provides a confidence measure on each reconstructed mesh triangle. Its input is a set of vision-based or Lidar-based 3D measurements which are converted to a set of mass functions that characterize the level of confidence on the occupancy of the scene as occupied, empty or unknown based on Dempster-Shafer Theory. The output is a multi-label segmentation of the ambient 3D space expressing the confidence for each resulting volume element to be occupied or empty. While existing methods either sacrifice watertightness (local methods) or need to introduce a smoothness prior (global methods), we derive a per-triangle confidence measure that is able to gradually characterize when the resulting surface patches are certain due to dense and coherent measurements and when these patches are more uncertain and are mainly present to ensure smoothness and/or watertightness. The surface mesh reconstruction is formulated as a global energy minimization problem efficiently optimized with the α-expansion algorithm. We claim that the resulting confidence measure is a good estimate of the local lack of sufficiently dense and coherent input measurements, which would be a valuable input for the next-best-view scheduling of a complementary acquisition. Beside the new formulation, the proposed approach achieves state-of-the-art results on surface reconstruction benchmark. It is robust to noise, manages high scale disparity and produces a watertight surface with a small Hausdorff distance in uncertainty area thanks to the multi-label formulation. By simply thresholding the result, the method shows a good reconstruction quality compared to local algorithms on high density data. This is demonstrated on a large scale reconstruction combining real-world datasets from airborne and terrestrial Lidar and on an indoor scene reconstructed from images. Numéro de notice : C2016-024 Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-319-54190-7_23 date de publication en ligne : 12/03/2017 En ligne : http://doi.org/10.1007/978-3-319-54190-7_23 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84627

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 Congrès : ISPRS Geospatial Week 2015 (28 septembre - 3 octobre 2015; La Grande Motte, France) , 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. XL-3-W3 Importance : pp 613 - 617 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] algorithme Graph-Cut [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] maillage par triangles [Termes descripteurs IGN] octree [Termes descripteurs IGN] reconstruction d'objet 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 Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprsarchives-XL-3-W3-613-2015 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

Extending α-expansion to a larger set of regularization functions / Mathias Paget (2015)  

Public Titre : Extending α-expansion to a larger set of regularization functions Type de document : Article/Communication Auteurs : Mathias Paget, Auteur ; Jean-Philippe Tarel, Auteur ; Laurent Caraffa , Auteur Congrès : ICIP 2015, IEEE International Conference on Image Processing (27 - 30 septembre 2015; Québec, Québec - Canada) , Commanditaire Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2015 Importance : pp 1051 - 1055 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] filtrage du bruit [Termes descripteurs IGN] méthode de réduction d'énergie Résumé : (auteur) Many problems of image processing lead to the minimization of an energy, which is a function of one or several given images, with respect to a binary or multi-label image. When this energy is made of unary data terms and of pairwise regularization terms, and when the pairwise regularization term is a metric, the multi-label energy can be minimized quite rapidly, using the so-called α-expansion algorithm. α-expansion consists in decomposing the multi-label optimization into a series of binary sub-problems called move. Depending on the chosen decomposition, a different condition on the regularization term applies. The metric condition for α-expansion move is rather restrictive. In many cases, the statistical model of the problem leads to an energy which is not a metric. Based on the enlightening article [1], we derive another condition for β-jump move. Finally, we propose an alternated scheme which can be used even if the energy fulfills neither the α-expansion nor β-jump condition. The proposed scheme applies to a much larger class of regularization functions, compared to α-expansion. This opens many possibilities of improvements on diverse image processing problems. We illustrate the advantages of the proposed optimization scheme on the image noise reduction problem. Numéro de notice : C2015-060 Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICIP.2015.7350960 date de publication en ligne : 10/12/2015 En ligne : https://doi.org/10.1109/ICIP.2015.7350960 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91815