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View point evaluation and streamline filtering for flow visualization

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4 Author(s)
Teng-Yok Lee ; Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA ; Mishchenko, O. ; Han-Wei Shen ; Crawfis, R.

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.

Published in:

Pacific Visualization Symposium (PacificVis), 2011 IEEE

Date of Conference:

1-4 March 2011