Tracking Space-Filling Features by Two-Step Optimization

We present a novel approach for tracking space-filling features, i.e., a set of features covering the entire domain. The assignment between successive time steps is determined by a two-step, global optimization scheme. First, a maximum-weight, maximal matching on a bi-partite graph is computed to provide one-to-one assignments between features of successive time steps. Second, events are detected in a subsequent step; here the matching step serves to restrict the exponentially large set of potential solutions. To this end, we compute an independent set on a graph representing conflicting event explanations. The method is evaluated by tracking dissipation elements, a structure definition from turbulent flow analysis.

[1]  Torsten Kuhlen,et al.  Tracking space-filling structures in turbulent flows , 2015, 2015 IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV).

[2]  Hans J. W. Spoelder,et al.  Visualization of time-dependent data with feature tracking and event detection , 2001, The Visual Computer.

[3]  Andrew V. Goldberg,et al.  An efficient cost scaling algorithm for the assignment problem , 1995, Math. Program..

[4]  Deborah Silver,et al.  Visualizing features and tracking their evolution , 1994, Computer.

[5]  Xin Wang,et al.  Tracking and Visualizing Turbulent 3D Features , 1997, IEEE Trans. Vis. Comput. Graph..