3D time varying datasets are difficult to visualize and analyze because of the immense amount of data involved. This is especially true when the datasets are turbulent with many evolving amorphous regions, as it is difficult to observe patterns and follow regions of interest. We present our volume based feature tracking algorithm and discuss how it can be used to help visualize and analyze large time varying datasets. We also address efficiency issues in dealing with massive time varying datasets.
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Silver et al. (1996) studied this question.
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