Tracking and visualizing turbulent 3D features

  • Silver D
  • Wang X
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Visualizing 3D time-varying fluid datasets is difficult because of
the immense amount of data to be processed and understood. These
datasets contain many evolving amorphous regions, and it is difficult to
observe patterns and visually follow regions of interest. In this paper,
we present a technique which isolates and tracks full-volume
representations of regions of interest from 3D regular and curvilinear
computational fluid dynamics datasets. Connected voxel regions
(“features”) are extracted from each time step and matched
to features in subsequent time steps. Spatial overlap is used to
determine the matching. The features from each time step are stored in
octree forests to speed up the matching process. Once the features have
been identified and tracked, the properties of the features and their
evolutionary history can be computed. This information can be used to
enhance isosurface visualization and volume rendering by color coding
individual regions. We demonstrate the algorithm on four 3D time-varying
simulations from ongoing research in computational fluid dynamics and
show how tracking can significantly improve and facilitate the
processing of massive datasets

Author-supplied keywords

  • CFD
  • Computer vision
  • Feature tracking
  • Isosurfaces
  • Multidimensional visualization
  • Scientific visualization
  • Volume rendering

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  • Deborah Silver

  • Xin Wang

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