Visualization of time-dependent data with feature tracking and event detection

This paper presents an innovative method to analyze and visualize time-dependent evolution of features. The analysis and visualization of time-dependent data are complicated because of the immense number of data involved. However, if the scientist's main interest is the evolution of certain features, it suffices to show the evolution of these features. The task of the visualization method is to extract the features from all frames, to determine the correspondences between features in successive frames, to detect significant events or stages in the evolution of the features, and, finally, to visualize the results. The method described here performs all these steps, and it is applied to a number of applications.