Gaussian mixture model based volume visualization

  title={Gaussian mixture model based volume visualization},
  author={Shusen Liu and Joshua A. Levine and Peer-Timo Bremer and Valerio Pascucci},
  journal={IEEE Symposium on Large Data Analysis and Visualization (LDAV)},
Representing uncertainty when creating visualizations is becoming more indispensable to understand and analyze scientific data. Uncertainty may come from different sources, such as, ensembles of experiments or unavoidable information loss when performing data reduction. One natural model to represent uncertainty is to assume that each position in space instead of a single value may take on a distribution of values. In this paper we present a new volume rendering method using per voxel Gaussian… CONTINUE READING
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