Energy-scale Aware Feature Extraction for Flow Visualization

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 dy...

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Bibliographic Details
Published inComputer graphics forum Vol. 30; no. 3; pp. 771 - 780
Main Authors Pobitzer, A., Tutkun, M., Andreassen, Ø., Fuchs, R., Peikert, R., Hauser, H.
Format Journal Article
LanguageEnglish
Published Oxford, UK Blackwell Publishing Ltd 01.06.2011
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ISSN0167-7055
1467-8659
DOI10.1111/j.1467-8659.2011.01926.x

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Summary: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.
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ArticleID:CGF1926
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ISSN:0167-7055
1467-8659
DOI:10.1111/j.1467-8659.2011.01926.x