Target motion analysis visualisation
APVis '05 proceedings of the 2005 Asia-Pacific symposium on Information visualisation - Volume 45
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A new method for the simplification of flow fields is presented. It isbased on continuous clustering. A well-known physical clusteringmodel, the Cahn Hillard model which describes phase separation, ismodified to reflect the properties of the data to be visualized. Clustersare defined implicitly as connected components of the positivityset of a density function. An evolution equation for this function isobtained as a suitable gradient flow of an underlying anisotropicenergy functional. Here, time serves as the scale parameter. Theevolution is characterized by a successive coarsening of patterns -the actual clustering - and meanwhile the underlying simulationdata specifies preferable pattern boundaries. Here we discuss theapplicability of this new type of approach mainly for flow fields,where the cluster energy penalizes cross streamline boundaries, butthe method also carries provisions in other fields as well. The clustersare visualized via iconic representations. A skeletonization algorithmis used to find suitable positions for the icons.