Visualizing features and tracking their evolution

We describe basic algorithms to extract coherent amorphous regions (features or objects) from 2 and 3D scalar and vector fields and then track them in a series of consecutive time steps. We use a combination of techniques from computer vision, image processing, computer graphics, and computational geometry and apply them to data sets from computational fluid dynamics. We demonstrate how these techniques can reduce visual clutter and provide the first step to quantifying observable phenomena. These results can be generalized to other disciplines with continuous time-dependent scalar (and vector) fields.<>