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Surface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF / Jules Morel in Computers and graphics, vol 74 (August 2018)
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[article]
Titre : Surface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF Type de document : Article/Communication Auteurs : Jules Morel, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur
Année de publication : 2018 Projets : DIABOLO / Packalen, Tuula Conférence : SMI 2018, Shape Modelling International 06/06/2018 08/06/2018 Lisbonne Portugal https://www.sciencedirect.com/journal/computers-and-graphics/special-issue/10RZ9DXPNK4 Article en page(s) : pp 44 - 55 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] approximation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] équation de Poisson
[Termes IGN] fonction de base radiale
[Termes IGN] jeu de données localisées
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de pointsRésumé : (auteur) This paper introduces a novel surface reconstruction method based on unorganized point clouds, which focuses on offering complete and closed mesh models of partially sampled object surfaces. To accomplish this task, our approach builds upon a known a priori model that coarsely describes the scanned object to guide the modeling of the shape based on heavily occluded point clouds. In the region of space visible to the scanner, we retrieve the surface by following the resolution of a Poisson problem: the surface is modeled as the zero level-set of an implicit function whose gradient is the closest to the vector field induced by the 3D sample normals. In the occluded region of space, we consider the a priori model as a sufficiently accurate descriptor of the shape. Both models, which are expressed in the same basis of compactly supported radial functions to ensure computation and memory efficiency, are then blended to obtain a closed model of the scanned object. Our method is finally tested on traditional testing datasets to assess its accuracy and on simulated terrestrial LiDAR scanning (TLS) point clouds of trees to assess its ability to handle complex shapes with occlusions. Numéro de notice : A2018-530 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cag.2018.05.004 Date de publication en ligne : 17/05/2018 En ligne : https://doi.org/10.1016/j.cag.2018.05.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91400
in Computers and graphics > vol 74 (August 2018) . - pp 44 - 55[article]Terrain model reconstruction from terrestrial LiDAR data using radial basis functions / Jules Morel in IEEE Computer graphics and applications, vol 37 n° 5 ([01/09/2017])
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[article]
Titre : Terrain model reconstruction from terrestrial LiDAR data using radial basis functions Type de document : Article/Communication Auteurs : Jules Morel, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur ; Cédric Vega
, Auteur
Année de publication : 2017 Projets : 2-Pas d'info accessible - article non ouvert / Packalen, Tuula Article en page(s) : pp 72 - 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fonction de base radiale
[Termes IGN] modèle numérique de terrainRésumé : (auteur) The presence of vegetation and the terrain topography itself generate strong occlusions causing large gaps in terrestrial laser scanning (TLS) data at the ground level as well as a risk of integrating above-ground objects. This article introduces a surface-approximation algorithm dedicated to extracting digital terrain models (DTMs) from terrestrial TLS data acquired in forest areas. The proposed method is based on the combination of a quadtree subdivision of space guided by the local density and distribution of data together with a surface modeling via radial basis functions, which are used as partitions of unity for merging local quadratic approximating patches. Numéro de notice : A2017-881 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/MCG.2017.3621225 Date de publication en ligne : 20/09/2017 En ligne : https://doi.org/10.1109/MCG.2017.3621225 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91402
in IEEE Computer graphics and applications > vol 37 n° 5 [01/09/2017] . - pp 72 - 84[article]
Titre : Surface reconstruction based on forest terrestrial LiDAR data Type de document : Thèse/HDR Auteurs : Jules Morel, Auteur ; Marc Daniel, Directeur de thèse ; Cédric Vega , Directeur de thèse ; Alexandra Bac, Directeur de thèse
Editeur : Aix-en-Provence : Université d'Aix-Marseille Année de publication : 2017 Importance : 178 p. Format : 21 x 30 cm Note générale : bibliographie
A dissertation presented to the Department of Mathématique et Informatique in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Computer ScienceLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] distribution de Poisson
[Termes IGN] données lidar
[Termes IGN] données TLS (télémétrie)
[Termes IGN] fonction de base radiale
[Termes IGN] interpolation
[Termes IGN] modélisation de la forêt
[Termes IGN] placette d'échantillonnage
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] structure de la végétationIndex. décimale : THESE Thèses et HDR Résumé : (auteur) In recent years, the capacity of LiDAR technology to capture detailed information about forests structure has attracted increasing attention in the field of forest science. In particular, the terrestrial LiDAR arises as a promising tool to retrieve geometrical characteristics of trees at a millimeter level. This thesis studies the surface reconstruction problem from scattered and unorganized point
clouds, captured in forested environment by a terrestrial LiDAR. We propose a sequence of algorithms dedicated to the reconstruction of forests plot attributes model: the ground and the woody structure of trees (i.e. the trunk and the main branches). In practice, our approaches model the surface with implicit function build with radial basis functions to manage the homogeneity and handle the noise of the sample data points. Our first focus is on the reconstruction of the ground surface whose level of detail is based on local complexity, through alternation between scale refinement, filtering and reconstruction. The result arises from the polygonization of the implicit function expressed as the merging of local approximations by compactly supported radial basis function used as partition of unity. Once the ground is modeled, the topology effects can be ignored in the following computation steps that focus on the modeling of trees. Traditionally, the processing of the woody part is achieved by a discrete reconstruction in the form of a stack of independent building blocks. From such a model, our approach developed for the ground is adapted to approximate the woody part of the tree by a more flexible continuous surface. Expressed as an implicit function, the tree model can be refined by an additional computational step in order to describe precisely the geometry. With this in mind, we propose a method dedicated to the fine reconstruction of occluded objects: from 3D samples presenting occlusions,
we use the previously described continuous model to guide a Poisson surface reconstruction. Thus, we guarantee the production of a watertight surface that approximates sharply the point cloud in the visible areas and extrapolates consistently the tree shape in the occlusions.Note de contenu : 1- Introduction
2- Terrestrial LiDAR scanning in forests
3- Survey on surface reconstruction
4- Reconstruction of open surface
5- Geometric model of trees
6- Reconstruction of partially occluded objects
7- Conclusion and perspectivesNuméro de notice : 25855 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : IMAGERIE Nature : Thèse française Note de thèse : PhD Thesis: Computer Science : Marseille : 2017 Organisme de stage : Institut Français de Pondichéri (Inde) nature-HAL : Thèse DOI : sans En ligne : http://www.theses.fr/2017AIXM0039 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95472 Aboveground-biomass estimation of a complex tropical forest in India using Lidar / Cédric Vega in Remote sensing, vol 7 n° 8 (August 2015)
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Titre : Aboveground-biomass estimation of a complex tropical forest in India using Lidar Type de document : Article/Communication Auteurs : Cédric Vega , Auteur ; Udayalakshmi Vepakomma, Auteur ; Jules Morel, Auteur ; Jean-Luc Bader, Auteur ; Gopalakrishnan Rajashekar, Auteur ; Chandra Shekhar Jha, Auteur ; Jérôme Ferêt, Auteur ; Christophe Proisy, Auteur ; Raphaël Pélissier, Auteur ; Vinay Kumar Dadhwal, Auteur
Année de publication : 2015 Projets : 3-projet - voir note / Packalen, Tuula Article en page(s) : pp 10607 - 10625 Note générale : bibliographie
The research has been supported by IFPCAR (Indo-French Promotion Center for Advanced Research) through the joint project number 4509-1 “Controlling for Uncertainty in Assessment of Forest Aboveground Biomass in the Western Ghats of India”between UMR AMAP, Montpellier and the National Remote Sensing Centre, Hyderabad. The authors also greatly acknowledge the French Institute of Pondicherry (IFP) for its financial support to Udayalakshmi Vepakomma for visiting IFPand for providing field control data from its long term monitoring plot in Uppangala.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse aérienne
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] Ghats occidentaux
[Termes IGN] Inde
[Termes IGN] pente
[Termes IGN] profil en travers
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] volume en boisRésumé : (auteur) Light Detection and Ranging (Lidar) is a state of the art technology to assess forest aboveground biomass (AGB). To date, methods developed to relate Lidar metrics with forest parameters were built upon the vertical component of the data. In multi-layered tropical forests, signal penetration might be restricted, limiting the efficiency of these methods. A potential way for improving AGB models in such forests would be to combine traditional approaches by descriptors of the horizontal canopy structure. We assessed the capability and complementarity of three recently proposed methods for assessing AGB at the plot level using point distributional approach (DM), canopy volume profile approach (CVP), 2D canopy grain approach (FOTO), and further evaluated the potential of a topographical complexity index (TCI) to explain part of the variability of AGB with slope. This research has been conducted in a mountainous wet evergreen tropical forest of Western Ghats in India. AGB biomass models were developed using a best subset regression approach, and model performance was assessed through cross-validation. Results demonstrated that the variability in AGB could be efficiently captured when variables describing both the vertical (DM or CVP) and horizontal (FOTO) structure were combined. Integrating FOTO metrics with those of either DM or CVP decreased the root mean squared error of the models by 4.42% and 6.01%, respectively. These results are of high interest for AGB mapping in the tropics and could significantly contribute to the REDD+ program. Model quality could be further enhanced by improving the robustness of field-based biomass models and influence of topography on area-based Lidar descriptors of the forest structure. Numéro de notice : A2015--081 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs70810607 Date de publication en ligne : 18/08/2015 En ligne : https://doi.org/10.3390/rs70810607 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84559
in Remote sensing > vol 7 n° 8 (August 2015) . - pp 10607 - 10625[article]Documents numériques
en open access
Aboveground-biomass estimation ... - pdf éditeurAdobe Acrobat PDF
contenu dans Proceedings of SilviLaser 2015, 14th conference on Lidar Applications for Assessing and Managing Forest Ecosystems, September 28-30, 2015 - La Grande Motte, France / Sylvie Durrieu (2015)![]()
Titre : Computation of tree volume from terrestrial LiDAR data Type de document : Article/Communication Auteurs : Jules Morel, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur
Editeur : Antony [France] : Institut national de recherche en sciences et technologies pour l’environnement et l’agriculture IRSTEA (2012-2019) Année de publication : 2015 Projets : 1-Pas de projet / Packalen, Tuula Conférence : SilviLaser 2015, 14th conference on Lidar Applications for Assessing and Managing Forest Ecosystems 28/09/2015 30/09/2015 La Grande Motte France open access proceedings Importance : pp 308 - 310 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] distribution de Poisson
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fonction de base radiale
[Termes IGN] placette d'échantillonnage
[Termes IGN] reconstruction d'objet
[Termes IGN] volume en boisRésumé : (auteur) This paper introduces a new method for the detailed estimation of volumes of individual trees from terrestrial laser scanner data. This method is based on adapted compactly supported radial basis function models together with a deformable models approach. Numéro de notice : C2015-043 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83731 Documents numériques
en open access
Computation of tree volumeAdobe Acrobat PDF PermalinkPermalink