Group Dynamics in Scientific Visualization

The ability to visually extract and track features is appealing to scientists in many simulations including flow fields. However, as the resolution of the simulation becomes higher, the number of features to track increases and so does the cost in large-scale simulations. Since many of these features act in groups, it seems more cost-effective to follow groups of features rather than individual ones. Very little work has been done for tracking groups of features. In this paper, we present the first full group tracking model in which we track groups (clusters) of features in time-varying 3D fluid flow simulations. Our model uses a clustering algorithm to group interacting features. We demonstrate our model on data output from a 3D simulation of wall bounded turbulent