Visualization Symposium, IEEE Pacific (2011)
Hong Kong, China
Mar. 1, 2011 to Mar. 4, 2011
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.
maximum entropy methods, data visualisation, flow visualisation, flow field, view point evaluation, streamline filtering, flow visualization, geometric primitive, occlusion, 3D streamline, view-dependent algorithm, Shannon entropy, vector complexity, entropy field, three dimensional volume, maximal entropy projection framebuffer, maximal entropy values, view-dependent streamline selection algorithm, viewpoint selection algorithm, Entropy, Streaming media, Complexity theory, Pixel, Tiles, Three dimensional displays, Tornadoes, I.3.3 [Computing Methodologies]: Computer Graphics—Picture/Image Generation
"View point evaluation and streamline filtering for flow visualization", Visualization Symposium, IEEE Pacific, vol. 00, no. , pp. 83-90, 2011, doi:10.1109/PACIFICVIS.2011.5742376