Seeding Strategies for 3D Flow Data


This paper presents two strategies for seeding streamlines in 3D flow fields. The first method is based on critical point analysis of the flow field to identify regions with important flow patterns that need to be presented. Different seeding templates are then used around the vicinity of the different critical points. The second method is based on filtering and allows the user to adjust the density of streamlines to represent regions with similar flow patterns. Here, every point is seeded and a streamline traced. Neighboring streamlines that have similar geometric paths are removed to reduce clutter. The second method does not require prior analysis of the flow field. The main advantages of these two methods are that they reduce clutter and yet capture the important flow features, and they also allow the user to control the global coverage of streamlines for an aesthetically pleasing result.


A pdf version of the paper is available.


Two randomly generated 3D flow data were used to initially test our seeding algorithm. They are available here for others to use as comparison. One has 5 critical points, while the other has 108 critical points. Both are in plot3d format. Vtk has readers for them.

Images: (Click on the image for a higher resolution image.)

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