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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

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 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

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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},

}






 Last Modified: Jean-Paul Balabanian, 2014-04-09