Image-Based Streamsurfaces

Streamsurfaces are of fundamental importance to visualization of flows. Among other features, they offer strong capabilities in revealing flow behavior (e.g., in the vicinity of vortices), and are an essential tool for the computation of 2D separatrices in vector field topology. Computing streamsurfaces is, however, typically expensive due to the difficult triangulation involved, in particular when triangle sizes are kept in the order of the size of a pixel. We investigate image-based approaches for rendering streamsurfaces without triangulation, and propose a new technique that renders them by dense streamlines. Although our technique does not perform triangulation, it does not depend on user parametrization to avoid noticeable gaps. Our GPU-based implementation shows that our technique provides interactive frame rates and low memory usage in practical applications. We also show that previous texture-based flow visualization approaches can be integrated with our method, for example, for the visualization of flow direction with line integral convolution.