Title
Stream Surface Parametrization by Flow-Orthogonal Front Lines
Abstract
The generation of discrete stream surfaces is an important and challenging task in scientific visualization, which can be considered a particular instance of geometric modeling. The quality of numerically integrated stream surfaces depends on a number of parameters that can be controlled locally, such as time step or distance of adjacent vertices on the front line. In addition there is a parameter that cannot be controlled locally: stream surface meshes tend to show high quality, well-shaped elements only if the current front line is “globally” approximately perpendicular to the flow direction. We analyze the impact of this geometric property and present a novel solution – a stream surface integrator that forces the front line to be perpendicular to the flow and that generates quad-dominant meshes with well-shaped and well-aligned elements. It is based on the integration of a scaled version of the flow field, and requires repeated minimization of an error functional along the current front line. We show that this leads to computing the 1-dimensional kernel of a bidiagonal matrix: a linear problem that can be solved efficiently. We compare our method with existing stream surface integrators and apply it to a number of synthetic and real world data sets. © 2012 Wiley Periodicals, Inc.
Year
DOI
Venue
2012
10.1111/j.1467-8659.2012.03177.x
Comput. Graph. Forum
Keywords
Field
DocType
stream surface parametrization,flow field,flow direction,flow-orthogonal front lines,front line,current front line,integrated stream surface,stream surface mesh,geometric modeling,geometric property,discrete stream surface,stream surface integrator,surface,solid
Kernel (linear algebra),Computer vision,Perpendicular,Polygon mesh,Parametrization,Computer science,Geometric modeling,Integrator,Theoretical computer science,Bidiagonal matrix,Minification,Artificial intelligence
Journal
Volume
Issue
ISSN
31
5
0167-7055
Citations 
PageRank 
References 
5
0.43
18
Authors
4
Name
Order
Citations
PageRank
Maik Schulze1443.84
Tobias Germer21478.02
Christian Rössl344933.65
Holger Theisel4147999.18