Optimal Reference Frames, Scalings, and Features in Visualization
In Visualization, the success or failure of an analysis often depends on the choice of some subtle parameters or design choices.
While simple heuristics are often sufficient, in some cases they make the analysis miserably fail. We present three approaches
in visualization where a careful choice of optimal parameters results in new algorithms:
- the choice of a reference frame for finding objective vortices in flow visualization,
- the choice of a scaling of high-dimensional data sets for finding linear projections to 2D in information visualization,
- the choice of a feature definition along with numerical extraction methods for visualizing recirculation phenomena in flows.