Energy-scale Aware Feature Extraction for Flow Visualization
Armin Pobitzer, Murat Tutkun, Øyvind
Andreassen, Raphael Fuchs, Ronald Peikert, Helwig Hauser
ARTICLE,
Computer Graphics Forum,
2011
AbstractIn the visualization of flow simulation data, feature detectors
often tend to result in overly rich response, making some sort of filtering
or simplification necessary to convey meaningful images. In this paper we
present an approach that builds upon a decomposition of the flow field
according to dynamical importance of different scales of motion energy.
Focusing on the high-energy scales leads to a reduction of the flow field
while retaining the underlying physical process. The presented method
acknowledges the intrinsic structures of the flow according to its energy
and therefore allows to focus on the energetically most interesting aspects
of the flow. Our analysis shows that this approach can be used for methods
based on both local feature extraction and particle integration and we
provide a discussion of the error caused by the approximation. Finally,
we illustrate the use of the proposed approach for both a local and a global
feature detector and in the context of numerical flow simulations.
Published
Computer Graphics Forum
Media
BibTeX
@article{pobitzer11energyScale,
author = {Armin Pobitzer and Murat Tutkun and {\O}yvind
Andreassen and Raphael Fuchs and Ronald Peikert and Helwig Hauser},
title = {Energy-scale Aware Feature Extraction for Flow Visualization},
year = {2011},
abstract = {In the visualization of flow simulation data, feature detectors
often tend to result in overly rich response, making some sort of filtering
or simplification necessary to convey meaningful images. In this paper we
according to dynamical importance of different scales of motion energy.
Focusing on the high-energy scales leads to a reduction of the flow field
while retaining the underlying physical process. The presented method
acknowledges the intrinsic structures of the flow according to its energy
and therefore allows to focus on the energetically most interesting aspects
of the flow. Our analysis shows that this approach can be used for methods
based on both local feature extraction and particle integration and we
provide a discussion of the error caused by the approximation. Finally,
we illustrate the use of the proposed approach for both a local and a global
feature detector and in the context of numerical flow simulations.},
journal = {Computer Graphics Forum},
volume = {30},
number = {3},
pages = {771--780},
url = {http://dx.doi.org/10.1111/j.1467-8659.2011.01926.x},
event = {EuroVis 2011},
location = {Bergen, Norway},
}
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