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Titre : Geo-information and computational geometry Type de document : Monographie Auteurs : Peter J. M. Van Oosterom, Éditeur scientifique ; M.J. Van Kreveld, Éditeur scientifique Editeur : Delft : Netherlands Geodetic Commission NGC Année de publication : 2006 Collection : Netherlands Geodetic Commission Green series num. 44 Importance : 51 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-90-6132-299-3 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatiale
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] données localisées
[Termes IGN] données topographiques
[Termes IGN] géomètrie algorithmique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] système d'information géographiqueRésumé : (Editeur) The contributions reflect the diversity of the possible interactions between computational geometry and GIS. The topics of the contributions range from overviews of relevant techniques and tools to solving specific spatial problems in either the object-based (vector) or field-based (raster) domain. This publication is a reflection of the different seminar contributions. The first paper 'Computational Geometry: its objectives and relation to GIS' is by Marc van Kreveld (Utrecht University). The analysis of algorithms involves understanding how efficiently an algorithm solves a problem. One of the main objectives of computational geometry is finding the most efficient algorithms for all sorts of geometric problems. He introduces the main concepts and ideas in computational geometry, including efficiency analysis, intractability, output-sensitive algorithms, and approximation algorithms. The basic problems of computational geometry all have a direct or indirect use to GIS. He also indicates why computational geometry is not as useful to GIS as it could be (complicated algorithms, focus on worst-case efficiency, and on well-defined, simple to state problems) and how this is currently improving (available software libraries, simpler algorithms provably efficient under realistic assumptions).
Mark de Berg (TU Eindhoven) addresses one of the issues to make computational geometry techniques more applicable in practice, namely the handling of large data sets that do not fit in main memory (as often more or less implicitly assumed in the description of many data structures and algorithms). In his paper 'I/O- and Cache-efficient Algorithms for Spatial Data', he explains how the hierarchical memory consisting of a disk, main memory, and several levels of cache should be included in data structure and algorithm design. The difference between the times to access these different levels of memory is quite large: the disk is typically about 100,000 times slower than accessing the main memory. In the paper some of the recent results that have been obtained on I/O- and cache-efficient algorithms are discussed with focus on spatial data.
One specific data structure, based on quad-edges, and applied to creating and editing three-dimensional models, is described by Christopher Gold and Rebecca Tse (University of Glamorgan, UK) in their paper 'Quad-Edges and Euler Operators for Automatic Building Extrusion Using LiDAR Data' (LIght Detection And Ranging). The long-term research objective for their models is to integrate man-made objects with the landscape, so that topological properties, such as connectedness, may be used in applications such as flood modeling. Man-made objects such as build-ings, as well as terrain elevation, should be extracted directly from LiDAR data. Their model is a triangle-based boundary description of the relevant objects and earth surface. The model creation and local modifications (updates) is performed on the Quad-Edge data structure by using Euler operators. These operators permit various extrusion operations as well as the manual insertion of bridges and tunnels.
A description of the use computational geometry tools used to solve a few specific cartographic problems is given by Bettina Speckmann (TU Eindhoven) in her paper 'Algorithms for cartograms and other specialized maps'. Cartograms are a useful and intuitive tool to visualize statistical data about a set of regions like countries, states or counties. The size of a region in a cartogram corresponds to a particular geographic variable and therefore the regions generally cannot keep both their shape and their adjacencies. A good cartogram, however, preserves the recognizability in some way. The paper gives a short overview of cartogram algorithms, and focuses in particular on the computation of rectangular cartograms. In a rectangular cartogram each region is represented by a rectangle. An implementation and various tests show that in practice, visually pleasing rectangular cartograms with small cartographic error can be generated effectively. Furthermore, the computation of proportional symbol maps is also discussed briefly.
Three-dimensional topographic modeling is also the topic of the paper by Friso Penninga (TU Delft): 'Constrained tetrahedral models and update algorithms for topographic data'. In contrast to the work of Gold and Tse he does not do this by representing the bounding surfaces, but he represents the three-dimensional objects by sets of tetrahedrons. The whole model then becomes a tetrahedronized irregular network (TEN), the 3D version of the more generally known triangulated irregular network (TIN). The TEN is a well-defined and robust data structure which enables complex processing by separate processing on each primitive first and afterwards joining all these partial results into a final result. In order to represent their borders several edges and faces will be handled as constraints. Updating a topographic dataset therefore equals the addition and removal of constraints within the network. One of the biggest challenges in the realization of such a data structure and corresponding algorithms is to reach acceptable performance, despite the potentially enormous amount of data. The last paper 'Towards improved solution schemes for Monte Carlo simulation in environmental modeling languages' is by Derek Karssenberg and Kor de Jong (Utrecht University). They deal with the field-based representation of spatial data, in contrast to the object-based representation of spatial data in the other papers. On the most often used field-based data structure, the regular grid, the algorithmic challenges are quite different than their counterparts in the object-based approaches. Environmental modeling languages such as PCRaster are programming languages embedded in GIS to simulate environmental processes. These languages are used to construct dynamic models, also called forward models, which are simulations run forward in time, where the state of the model at time t is defined as a function of its state in a time step preceding t. For future applications, at least two extensions to the languages are required: support of three spatial dimensions (as the real world is often 3D), and inclusion of Monte Carlo simulation techniques (to calculate how input errors propagate to the output of a model).Note de contenu : Editorial - Peter van Oosterom and Marc van Kreveld
- Computational Geometry: Ils objectives and relation to GIS - Marc van Kreveld
- I/O- and Cache-Efficient Algorithms for Spatial Data - Mark de Berg
- Quad-Edges and Euler Operators for Automatic Building Extrusion Using LIDAR Data - Christopher
Gold and Rebecca Tse
- Algorithms for cartograms and other specialized maps - Bettina Speckmann
- Constrained tetrahedral models and update algorithms for topographie data - Friso Penninga
- Towards improved solution schemes for Monte Carlo simulation in environmental modeling languages - Derek Karssenberg and Kor de JongNuméro de notice : 15213 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif En ligne : https://www.ncgeo.nl/index.php/en/publicatiesgb/green-series/item/2363-gs-44-pet [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=55100 Réservation
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Geo-information and computational geometry - pdf éditeurAdobe Acrobat PDF Improving building footprints in InSAR data comparison with a Lidar DSM / Paolo Gamba in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 1 (January 2006)
[article]
Titre : Improving building footprints in InSAR data comparison with a Lidar DSM Type de document : Article/Communication Auteurs : Paolo Gamba, Auteur ; F. Dell'acqua, Auteur ; G. Lisini, Auteur ; F. Cisotta, Auteur Année de publication : 2006 Article en page(s) : pp 63 - 70 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] correction géométrique
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] étalement d'histogramme
[Termes IGN] image 3D
[Termes IGN] image radar moirée
[Termes IGN] milieu urbain
[Termes IGN] modèle numérique de surfaceRésumé : (Auteur) The first aim of this paper is to show how the joint use of Digital Surface Models (Dsms) coming from different sources may improve the understanding of an urban environment. More specifically, we consider laser and radar three-dimensional data over the same urban area and show that they can be profitably combined to improve building extraction. We exploit the better vertical and horizontal accuracy of the laser DSM, assumed to be available only for a small area, to ease the deformation of Interferometric Synthetic Aperture Radar (INSAR) DSM with built structures. To achieve this, we propose a method based on subsequent steps of geometrical correction, and mainly on a simple "stretching step" that uses laser data as a reference to adjust INSAR-derived building footprints. We show quantitative results obtained from two different urban areas, using different laser and radar data sets, to assess advantages and drawbacks of the proposed method. Numéro de notice : A2006-002 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.1.63 En ligne : https://doi.org/10.14358/PERS.72.1.63 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27730
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 1 (January 2006) . - pp 63 - 70[article]Recognition of Building Roof Facets by Merging Aerial Images and 3D Lidar Data in a Hierarchical Segmentation Framework / Frédéric Bretar (2006)
Titre : Recognition of Building Roof Facets by Merging Aerial Images and 3D Lidar Data in a Hierarchical Segmentation Framework Type de document : Article/Communication Auteurs : Frédéric Bretar, Auteur ; Marc Pierrot-Deseilligny , Auteur ; Michel Roux, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2006 Conférence : ICPR 2006, 18th International Conference on Pattern Recognition 20/08/2006 24/08/2006 Hong Kong Hong Kong Proceedings IEEE Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fusion de données
[Termes IGN] image aérienne à axe vertical
[Termes IGN] segmentation hiérarchique
[Termes IGN] toitRésumé : (auteur) We investigate in this paper an original methodology for detecting roof facets through the fusion of aerial images and lidar data (3D point cloud). Based on a hierarchical segmentation of the image, we define a cost function that manages the merging order of regions. It depends on both radio-metric similarities of two neighbouring regions as well as on extracted information from lidar data. Considering that lidar data have been filtered into points belonging either to ground or non-ground classes, we define semantic and geometric rules in the binary merging process. Building roof facets are finally detected by selecting a level of generality for representing roof building components. Some remarks are given concerning the reliability of the integration of lidar and image data. Reconstructed roof facets are finally shown onto complex buildings. Numéro de notice : C2006-049 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICPR.2006.970 Date de publication en ligne : 18/09/2006 En ligne : https://doi.org/10.1109/ICPR.2006.970 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103381
Titre : Tree detection in aerial LIDAR and image data Type de document : Article/Communication Auteurs : John Secord, Auteur ; Avideh Zahkor, Auteur Editeur : New York [Etats-Unis] : IEEE Signal Processing Society Année de publication : 2006 Conférence : ICIP 2006, 13th IEEE International Conference on Image Processing 08/10/2006 11/10/2006 Atlanta Géorgie - Etats-Unis Proceedings IEEE Importance : 35 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage dirigé
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] modélisation 3D
[Termes IGN] segmentationRésumé : (auteur) In this paper, we present an approach to detecting trees in registered aerial image and range data obtained via LiDAR. The motivation for this problem comes from automated city modeling, in which such data is used to generate textured 3-D models. Representing the trees in these models is problematic because the data is usually too sparsely sampled in tree regions to create an accurate 3-D model of the trees. Furthermore, including the tree data points interferes with the polygonization step of the building roof top models. Therefore, it is advantageous to detect and remove points that represent trees in both LiDAR and aerial imagery. In this paper, we propose a two-step method for tree detection consisting of segmentation followed by classification. The segmentation is done using a simple region-growing algorithm using weighted features from aerial image and LiDAR, such as height, texture map, height variation, and normal vector estimates. The weights for the features are determined using a learning method on random walks. The classification is done using weighted support vector machines (SVM), allowing us to control the misclassification rate. The overall problem is formulated as a binary detection problem, and receiver operating characteristic curves are shown to validate our approach. Numéro de notice : C2006-024 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication DOI : 10.1109/ICIP.2006.312850 En ligne : https://doi.org/10.1109/ICIP.2006.312850 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90963
Titre : Viewing planning for range acquisition in indoor environments Type de document : Thèse/HDR Auteurs : Kok-Lim Low, Auteur Editeur : Chapel Hill [USA] : University of North Carolina Année de publication : 2006 Importance : 199 p. Format : 21 x 30 cm Note générale : bibliographie
A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in
partial fulfillment of the requirements for the degree of Doctor of Philosophy in the
Department of Computer Science.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] acquisition simultanée
[Termes IGN] algorithme de fusion
[Termes IGN] algorithme ICP
[Termes IGN] approche hiérarchique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] positionnement en intérieur
[Termes IGN] programmation par contraintes
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] scène intérieureRésumé : (auteur) This dissertation presents a new and efficient next-best-view algorithm for 3D reconstruction of indoor environments using active range sensing. A major challenge in range acquisition for 3D reconstruction is an efficient automated view planning algorithm to determine a sequence of scanning locations or views such that a set of acquisition constraints and requirements is satisfied and the object or environment of interest can be satisfactorily reconstructed. Due to the intractability of the view planning problem and the lack of global geometric information, a greedy approach is adopted to approximate the solution. A practical view metric is formulated to include many real-world acquisition constraints and reconstruction quality requirements. This view metric is flexible to allow trade-offs between different requirements of the reconstruction quality. A major contribution of this work is the application of a hierarchical approach to greatly accelerate the evaluation of the view metric for a large set of views. This is achieved by exploiting the various spatial coherences in the acquisition constraints and reconstruction quality requirements when evaluating the view metric. The hierarchical view evaluation algorithm is implemented in a view planning system targeted for the acquisition of indoor environments using a monostatic range scanner with 3D pose. The results show great speedups over the straightforward method used in many previous algorithms. The view planning system has also been shown to be robust for realworld application. The dissertation also describes how the view metric can be generalized to incorporate general acquisition constraints and requirements, and how the hierarchical view evaluation algorithm can be generalized to scanners with general pose, and to scanners with bistatic sensors. A simple extension is also proposed to enable the hierarchical view evaluation algorithm to take into account each view’s sensitivity to the potential pose errors in the physical positioning of the scanner. A computed new view must produce a range image that can be accurately registered to the previous scans. In this work, a metric is developed to estimate the registration accuracy of the views. This metric considers the amount of overlap, the range measurement errors, and the shape complexity of the surfaces. Note de contenu : 1- Introduction
2- Background
3- A Next-Best-View Solution
4- View evaluation
5- Surface Registration
6- Results
7- ConclusionNuméro de notice : 24637 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Computer Science : Chapel Hill - North Carolina : 2006 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92241 Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 24637-01 THESE Livre LASTIG Dépôt en unité Exclu du prêt Documents numériques
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Viewing planning for range... - pdf auteurAdobe Acrobat PDF Integrating LIDAR elevation data, multi-spectral imagery and neural network modelling for marsh characterization / J.T. Morris in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)PermalinkLidar validation using GIS : a case study comparison between two Lidar collection methods / T.L. Webster in Geocarto international, vol 20 n° 4 (December 2005 - February 2006)PermalinkPermalinkEffects of laser beam alignment tolerance on lidar accuracy / D. Latypov in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 6 (November 2005)PermalinkEstimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data / Z.J. Bortolot in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 6 (November 2005)PermalinkTime-space modelling with terrestrial Lidar: monitoring ice cliff evolution of the glacier, Italy with ILRS-3D / A. Tamburini in GIM international, vol 19 n° 11 (November 2005)PermalinkLidar elevation data for surface hydrologic modeling: resolution and representation issues / C. Barber in Cartography and Geographic Information Science, vol 32 n° 4 (October 2005)PermalinkNew approach to geodata representation with Geokosmos: technology based on airborne Lidar & digital aerial photography / E. Medvedev in Geoinformatics, vol 8 n° 5 (01/08/2005)PermalinkDEM generation and building detection from Lidar data / R. Ma in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 7 (July 2005)PermalinkLidar on the level in Afghanistan: GPS, inertial map the Kabul road / S. Newby in GPS world, vol 16 n° 7 (July 2005)Permalink