T. Salzbrunn, A. Wiebel, and G. Scheuermann (Germany)
Scientific and mathematical visualization, flow visualiza tion, feature detection
Visualizing flow structures according to the users’ inter ests provides insight to scientists and engineers. In previ ous work, a flow structure based on streamline predicates, that examine, whether a streamline has a given property, was defined. Evaluating all streamlines results in charac teristic sets grouping all streamlines with similar behavior with respect to a given predicate. Since there are infinitely many streamlines, the algorithm chooses a finite subset for the computation of an approximated discrete version of the characteristic sets. However, even the construction of char acteristic sets based on a finite set of streamlines tends to be computationally expensive. Based on a thorough analysis of all processing steps, we present and compare different acceleration approaches. The techniques are based on sim plifications that result in characteristic set boundaries devi ating from the correct but computational expensive bound aries. We develop measures for objective comparison of the introduced errors. An adaptive refinement approach turns out to be the best compromise between computation time and quality.
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