Mathematical foundations of scientific visualization, computer graphics, and massive data exploration

Visualization is one of the most active and exciting areas of Mathematics and Computing Science, and indeed one which is only beginning to mature. Current visualization algorithms break down for very large data sets. While present approaches use multi-resolution ideas, future data sizes will not be...

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Détails bibliographiques
Auteur principal: Möller, Torsten, informaticien
Autres auteurs: Hamann, Bernd (Directeur de la publication), Russell, Robert D. (Directeur de la publication)
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Édition:1st ed. 2009.
Collection:Mathematics and Visualization
Accès en ligne:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Note: Description d'après consultation du 26 mars 2012
Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration, Texte imprimé, 9783540860785
• Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration, Texte imprimé, 9783642064142
• Mathematical foundations of scientific visualization, computer graphics, and massive data exploration, Torsten Möller, Bernd Hamann, Robert Russell, editor, 2009, [Berlin], Springer, 1 vol. (VII-350 p.), Mathematics and vizualisation, 978-3-540-25076-0
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100 1 |a Möller, Torsten,  |c informaticien. 
245 1 0 |a Mathematical foundations of scientific visualization, computer graphics, and massive data exploration   |c Torsten Möller, Bernd Hamann, Robert Russell. 
250 |a 1st ed. 2009. 
260 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg. 
260 |a Cham :  |b Springer Nature,  |c [20..]. 
490 0 |a Mathematics and Visualization  |x 2197-666X 
500 |a Description d'après consultation du 26 mars 2012 
500 |a Archives Springer e-books (Licence nationale) 
500 |a Archives Springer e-books (Licence nationale) 
504 |a Bibliogr. Index 
505 1 |a 1. Maximizing Adaptivity in Hierarchical Topological Models Using Cancellation Trees Peer-Timo Bremer, Valerio Pascucci, and Bernd Hamann 2. The TOPORRERY: computation and presentation of multi-resolution topology Valerio Pascucci, Kree Cole-McLaughlin, and Giorgio Scorzelli 3. Isocontour based Visualization of Time-varying Scalar Fields Ajith Mascarenhas, and Jack Snoeyink 4. DeBruijn Counting for Visualization Algorithms David C. Banks and Paul K. Stockmeyer 5. Topological Methods for Visualizing Vortical Flows Xavier Tricoche and Christoph Garth 6. Stability and Computation of Medial Axes - a State-of-the-Art Report Dominique Attali, Jean-Daniel Boissonnat, and Herbert Edelsbrunner 7. Local Geodesic Parametrization: An Ant's Perspective Lior Shapira and Ariel Shamir 8. Tensor-fields Visualization using a Fabric like Texture to Arbitrary two-dimensional Surfaces Ingrid Hotz, Louis Feng, Bernd Hamann, and Kenneth Joy 9. Flow Visualization via Partial Differential Equations T. Preusser, M. Rumpf, and A. Telea 10. Iterative Twofold Line Integral Convolution for Texture-Based Vector Field Visualization Daniel Weiskopf 11. Constructing 3D Elliptical Gaussians for Irregularly Gridded Data Wei Hong, Neophytos Neophytou, Klaus Mueller and Arie Kaufman 12. From Sphere Packing to the Theory of Optimal Lattice Sampling Alireza Entezari, Ramsay Dyer, and Torsten Möller 13. Reducing Interpolation Artifacts by Globally Fairing Contours Martin Bertram and Hans Hagen 14. Time- and Space-efficient Error Calculation for Multiresolution Direct Volume Rendering Attila Gyulassy, Lars Linsen, and Bernd Hamann 15. Massive Data Visualization: A Survey Kenneth I. Joy 16. Compression and Occlusion Culling for Fast Isosurface Extraction from Massive Datasets Benjamin Gregorski, Joshua Senecal, Mark Duchaineau, and Kenneth I. Joy 17. Volume Visualization of Multiple Alignment of Large Genomic DNA Nameeta Shah, Scott E. Dillard, Gunther H. Weber, Bernd Hamann 18. Model-based Visualization - Computing Perceptually Optimal Visualizations J.J. van Wijk 
506 |a Accès en ligne pour les établissements français bénéficiaires des licences nationales 
506 |a Accès soumis à abonnement pour tout autre établissement 
506 |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 
520 |a Visualization is one of the most active and exciting areas of Mathematics and Computing Science, and indeed one which is only beginning to mature. Current visualization algorithms break down for very large data sets. While present approaches use multi-resolution ideas, future data sizes will not be handled that way. New algorithms based on sophisticated mathematical modeling techniques must be devised which will permit the extraction of high-level topological structures that can be visualized. For these reasons a workshop was organized at the Banff International Research Station, focused specifically on mathematical issues. A primary objective of the workshop was to gather together a diverse set of researchers in the mathematical areas relevant to the recent advances in order to discuss the research challenges facing this field in the next several years. The workshop was organized into five different thrusts: - Topology and Discrete Methods - Signal and Geometry Processing - Partial Differential Equations - Data Approximation Techniques - Massive Data Applications This book presents a summary of the research ideas presented at this workshop 
700 1 |a Hamann, Bernd.  |4 pbd 
700 1 |a Russell, Robert D.  |4 pbd 
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