Numerical simulations of global warming, Mars observation data, and aircraft design are but a few of the topics where the use of human visual perception for data understanding are considered essential. Ten years agoa handful of pioneers professed the value of visualization to skeptical audiences. Today, with supercomputers and sensors producing ever-increasing amounts of data, scientific visualization is accepted throughout much of science and engineering as the fundamental tool for data analysis. Written by a world-wide panel of visualization experts, Scientific Visualization: Advances and Challenges presents astute coverage of prevailing trends, issues, and practice of scientific visualization. From algorithmic topics such as volume graphics and the modeling and visualization of large data sets, to foundations, perception, and interface technology (including virtual reality), this book provides the latest advances in the area. The book demonstrates new techniques, examines diverse application areas, and discusses current limitations and upcoming requirements. Scientific Visualization:Advances and Challenges $> presents readers with a unique opportunity to examine expert thinking and current practice, and to obtain a vision of potential future directions. It will be essential reading for scientific and engineering practitioners and visualization researchers alike.
Recenzijos
Larry Rosenblum and many of his collaborators in the collection Scientific Visualization: Advances and Challenges were critical participants in the subsequent movement to define the field and to help it evolve from a hodge-podge of heuristics toward its deeper conceptual roots. The nominal goal of this book is to provide a broad picture of the current state of the art--a checkpoint on what has happened since 1987--to scientists with a vested interest in visualization methods. In this it largely succeeds....Scientific Visualization: Advances and Challenges provides a look at the global issues that are significant for visualization science, as well as getting down to detailed examples in several areas. --IEEE COMPUTATIONAL SCIENCE & ENGINEERING
Volume Visualization: A. Kaufman,<$> Trends in Volume Visualization and
Volume Graphics. K.H. Hihne, A. Pommort, M. Riemer, T. Schiemann, R.
Schubert, and U. Tiede,<$> Medical Volume Visualization Based on Intelligent
Volumes. W. Kruger and P. Schroder,<$> Data Parallel Volume Rendering.
Interface Technology and Perception:<$> J. Encarnacao and M. Fruhauf,<$>
Global Information Visualization--The Visualization Challenge for the 21st
Century. S. Bryson,<$> Real-Time Exploratory Scientific Visualization and
Virtual Reality. C. Beshers and S. Feiner,<$> Automated Design of Data
Visualizations. J. Foley and B. Ribarsky,<$> Next-generation Data
Visualization Tools. N. Gershon,<$> From Perception to Visualization.
Visualizing Large Data Sets:<$> G. Nielson,<$> Research Issues in Modeling
for the Analysis and Visualization of Large Data Sets. P. Brunet, R. Juan, I.
Navazo, A. Puig, J. Sole, and D. Tost,<$> Modeling and Visualization Through
Data Compression. M. Gross,<$> Subspace Methods for the Visualization of
Multidimensional Data Sets. H. Hagen,<$> Visualization of Large Data Sets.
Foundations and Systems:<$> N.M. Thalmann and D. Thalmann,<$> Computer
Animation: A Key Issue forTime Visualization. R.A. Earnshaw and M. Jern,<$>
Fundamental Approaches to Interactive Real-Time Visualization Systems. J.
Gallop,<$> Underlying Data Models and Structures for Visualization. S.
Causse, F. Juaneda, and M. Grave,<$> Partitioned Objects Sharing for
Visualization in Distributed Environments. T. Fruhauf, M. Gibel, H. Haase,
and K. Karlsson,<$> Design of a Flexible Monolithic Visualization System. P.
Robertson and L. De Ferrari,<$> Systematic Approaches to Visualization: Is a
Reference Model Needed? Modeling Complexity:<$> Y. Shinagawa, T. Kunii, A.
Fomenko, and S. Takahashi,<$> Coding of Object Surfaces Using Atoms. M.
Novak,<$> Fractal Geometry and Its Applications in Visualization. J.
Rossignac,<$> Representing and Visualizing Complex Continuous Geometric
Models. A. Gagalowicz,<$> Modeling Complex Indoor Scenes Using an
Analysis/Synthesis Framework. Applications:<$> F. Post and J. van Wijk,<$>
Visual Representation of Vector Fields: Recent Developments and Research
Directions. D.I. Abramov, V.V. Gusev, S.V. Klimenko, W. Kruger, L.I.
Ponomarev, and W. Renz,<$> Visualization of the Quantum Coulomb Three-Body
Problem in the Adiabatic Hyperspherical Approach. E. De Jong,<$> Solar System
Visualization:Global Science Maps. L. Hesselink and T. Delmarcelle,<$>
Visualization of Vector and Tensor Data Sets. L.J. Rosenblum and B.
Kamgar-Parsi,<$> Progress and Problems in Ocean Visualization. L.J.
Rosenblum,<$> Research Issues in Scientific Visualization.<$> Appendix.
Subject Index.
Rae Earnshaw is Head of the Electronic Imaging and Media Communications unit at the University of Bradford, with interests in graphics algorithms, scientific visualization, graphics standards, workstations and display technology, multimedia, CAD/CAM, graphics systems building, education issues and human-computer interface issues. He has been a Visiting Professor at Illinois Institute of Technology, Chicago, NorthwesternPolytechnical University, China, and George Washington University, Washington DC. He was a Director of the NATO Advanced Study Institute on Theoretical Foundations of Computer Graphics and CAD held in Italy in 1987. He is a member of the ACM, IEEE, CGS,EG, and a Fellow of the British Computer Society. Earnshaw has authored and edited 18 books on graphics algorithms, computer graphics, visualization, and associated topics, and published a number of papers in these areas. Professor Earnshaw is a member ofthe Editorial Board of The Visual Computer, Vice-President of the Computer Graphics Society, and Chair of the British Computer Society Computer Graphics and Displays Group.
