Fr. 189.00

Topology-based Methods in Visualization

English · Paperback / Softback

Shipping usually within 6 to 7 weeks

Description

Read more

Enabling insight into large and complex datasets is a prevalent theme in visualization research for which different approaches are pursued.
Topology-based methods are built on the idea of abstracting characteristic structures such as the topological skeleton from the data and to construct the visualizations accordingly. There are currently new demands for and renewed interest in topology-based visualization solutions. This book presents 13 peer-reviewed papers as written results from the 2005 workshop "Topology-Based Methods in Visualization" that was initiated to enable additional stimulation in this field. It contains a longer chapter dedicated to a survey of the state-of-the-art, as well as a great deal of original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in topology-based visualization research.

List of contents

Topology-Based Flow Visualization, The State of the Art.- Topology-guided Visualization of Constrained Vector Fields.- Scale-Space Tracking of Critical Points in 3D Vector Fields.- Feature Flow Fields in Out-of-Core Settings.- Streamline Predicates as Flow Topology Generalization.- Topology-based versus Feature-based Flow Analysis - Challenges and an Application.- Topology Based Flow Analysis and Superposition Effects.- On the Applicability of Topological Methods for Complex Flow Data.- Extraction and Visualization of Swirl and Tumble Motion from Engine Simulation Data.- Simulation Methods for Advanced Design Engineering.- A Practical Approach to Two-Dimensional Scalar Topology.- On the Role of Topology in Focus+Context Visualization.- N-dimensional Data-Dependent Reconstruction Using Topological Changes.

About the author

Hans Hagen, geboren 1955 in den Niederlanden, liebt das Reisen und lässt sich von fremden Kulturen zu den Geschichten seiner Bücher inspirieren.

Summary

Enabling insight into large and complex datasets is a prevalent theme in visualization research for which different approaches are pursued.
Topology-based methods are built on the idea of abstracting characteristic structures such as the topological skeleton from the data and to construct the visualizations accordingly. There are currently new demands for and renewed interest in topology-based visualization solutions. This book presents 13 peer-reviewed papers as written results from the 2005 workshop “Topology-Based Methods in Visualization” that was initiated to enable additional stimulation in this field. It contains a longer chapter dedicated to a survey of the state-of-the-art, as well as a great deal of original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in topology-based visualization research.

Product details

Assisted by Han Hagen (Editor), Hans Hagen (Editor), Helwig Hauser (Editor), Holger Theisel (Editor)
Publisher Springer, Berlin
 
Languages English
Product format Paperback / Softback
Released 06.10.2010
 
EAN 9783642089770
ISBN 978-3-642-08977-0
No. of pages 222
Dimensions 155 mm x 12 mm x 235 mm
Weight 359 g
Illustrations X, 222 p.
Series Mathematics and Visualization
Mathematics and Visualization
Subjects Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics

C, Topologie, Mathematics, Visualization, Mathematics and Statistics, Computer Graphics, Topology, Data and Information Visualization, Graphics programming

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.