A flow-guided streamline seeding strategy
Vivek Verma, David Peter Kao, Alex Pang · 2000
This paper presents a seed placement strategy for streamlines based on ow features in the data set. The primary goal of our seeding strategy is to capture ow patterns in the vicinity of critical points in the ow eld, even as the density of streamlines is reduced. Secondary goals are to place streamlines such that there is sucient coverage in non-critical regions, and to vary the streamline placements and lengths so that the overall presentation is aesthetically pleasing (avoid clustering of streamlines, avoid sharp discontinuities across several streamlines, etc.). The procedure is straight forward and non-iterative. First, critical points are identied. Next, the ow eld is segmented into regions, each containing a single critical point. The critical point in each region is then seeded with a template depending on the type of critical point. Finally, additional seed points are randomly distributed around the eld using a Poisson disk distribution to minimize closely spaced seed points. The main advantage of this approach is that it does not miss the features around critical points. Since the strategy is not image-guided, and hence not view dependent, signicant savings are possible when examining ow elds from dierent viewpoints, especially for 3D ow elds. Key Words and Phrases: seed placement, streamline, critical point, Voronoi diagram, Poisson disk distribution. 1