View point evaluation and streamline filtering for flow visualization

Visualization of flow fields with geometric primitives is often challenging due to occlusion that is inevitably introduced by 3D streamlines. In this paper, we present a novel view-dependent algorithm that can minimize occlusion and reveal important flow features for three dimensional flow fields. T...

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Vydáno v:2011 IEEE Pacific Visualization Symposium s. 83 - 90
Hlavní autoři: Teng-Yok Lee, Mishchenko, Oleg, Han-Wei Shen, Crawfis, Roger
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.03.2011
Témata:
Complexity theory
Entropy
I.3.3 [Computing Methodologies]: Computer Graphics-Picture/Image Generation
Pixel
Streaming media
Three dimensional displays
Tiles
Tornadoes
ISBN:1612849350, 9781612849355
ISSN:2165-8765
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Abstract Visualization of flow fields with geometric primitives is often challenging due to occlusion that is inevitably introduced by 3D streamlines. In this paper, we present a novel view-dependent algorithm that can minimize occlusion and reveal important flow features for three dimensional flow fields. To analyze regions of higher importance, we utilize Shannon's entropy as a measure of vector complexity. An entropy field in the form of a three dimensional volume is extracted from the input vector field. To utilize this view-independent complexity measure for view-dependent calculations, we introduce the notion of a maximal entropy projection (MEP) framebuffer, which stores maximal entropy values as well as the corresponding depth values for a given viewpoint. With this information, we develop a view-dependent streamline selection algorithm that can evaluate and choose streamlines that will cause minimum occlusion to regions of higher importance. Based on a similar concept, we also propose a viewpoint selection algorithm that works hand-in-hand with our streamline selection algorithm to maximize the visibility of high complexity regions in the flow field.
AbstractList Visualization of flow fields with geometric primitives is often challenging due to occlusion that is inevitably introduced by 3D streamlines. In this paper, we present a novel view-dependent algorithm that can minimize occlusion and reveal important flow features for three dimensional flow fields. To analyze regions of higher importance, we utilize Shannon's entropy as a measure of vector complexity. An entropy field in the form of a three dimensional volume is extracted from the input vector field. To utilize this view-independent complexity measure for view-dependent calculations, we introduce the notion of a maximal entropy projection (MEP) framebuffer, which stores maximal entropy values as well as the corresponding depth values for a given viewpoint. With this information, we develop a view-dependent streamline selection algorithm that can evaluate and choose streamlines that will cause minimum occlusion to regions of higher importance. Based on a similar concept, we also propose a viewpoint selection algorithm that works hand-in-hand with our streamline selection algorithm to maximize the visibility of high complexity regions in the flow field.
Author Mishchenko, Oleg
Crawfis, Roger
Han-Wei Shen
Teng-Yok Lee
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  givenname: Oleg
  surname: Mishchenko
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  email: mishchen@cse.ohio-state.edu
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  surname: Han-Wei Shen
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  surname: Crawfis
  fullname: Crawfis, Roger
  email: crawfis@cse.ohio-state.edu
  organization: Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA
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Snippet Visualization of flow fields with geometric primitives is often challenging due to occlusion that is inevitably introduced by 3D streamlines. In this paper, we...
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StartPage 83
SubjectTerms Complexity theory
Entropy
I.3.3 [Computing Methodologies]: Computer Graphics-Picture/Image Generation
Pixel
Streaming media
Three dimensional displays
Tiles
Tornadoes
Title View point evaluation and streamline filtering for flow visualization
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