Sets of Globally Optimal Stream Surfaces for Flow Visualization

Stream surfaces are a well‐studied and widely used tool for the visualization of 3D flow fields. Usually, stream surface seeding is carried out manually in time‐consuming trial and error procedures. Only recently automatic selection methods were proposed. Local methods support the selection of a set...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computer graphics forum Jg. 33; H. 3; S. 1 - 10
Hauptverfasser: Schulze, M., Esturo, J. Martinez, Günther, T., Rössl, C., Seidel, H.-P., Weinkauf, T., Theisel, H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Blackwell Publishing Ltd 01.06.2014
Schlagworte:
3-D graphics
Analysis
and systems
Categories and Subject Descriptors (according to ACM CCS)
Computer graphics
Computer Science
Computer simulation
Datalogi
Flow visualization
Fluids
I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Geometric algorithms
I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Geometric algorithms, languages, and systems
Image processing systems
languages
Mathematical analysis
Nucleation
Optimization
SRA - E-Science (SeRC)
SRA - E-vetenskap (SeRC)
Streams
Studies
Three dimensional
ISSN:0167-7055, 1467-8659, 1467-8659
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Stream surfaces are a well‐studied and widely used tool for the visualization of 3D flow fields. Usually, stream surface seeding is carried out manually in time‐consuming trial and error procedures. Only recently automatic selection methods were proposed. Local methods support the selection of a set of stream surfaces, but, contrary to global selection methods, they evaluate only the quality of the seeding lines but not the quality of the whole stream surfaces. Global methods, on the other hand, only support the selection of a single optimal stream surface until now. However, for certain flow fields a single stream surface is not sufficient to represent all flow features. In our work, we overcome this limitation by introducing a global selection technique for a set of stream surfaces. All selected surfaces optimize global stream surface quality measures and are guaranteed to be mutually distant, such that they can convey different flow features. Our approach is an efficient extension of the most recent global selection method for single stream surfaces. We illustrate its effectiveness on a number of analytical and simulated flow fields and analyze the quality of the results in a user study.
Bibliographie:ark:/67375/WNG-JS2QZN7F-6
Supporting InformationSupporting InformationSupporting Information
istex:096DFEC164E212FB212331AEE12E21A60027A232
ArticleID:CGF12356
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0167-7055
1467-8659
1467-8659
DOI:10.1111/cgf.12356