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This paper presents an interactive transfer function design tool based on ellipsoidal Gaussian transfer functions (ETFs). Our approach explores volumetric features in the statistical space by modeling the space using the Gaussian mixture model (GMM) with a small number of Gaussians to maximize the likelihood of feature separation. Instant visual feedback is possible by mapping these Gaussians to ETFs...
The use of multi-dimensional transfer functions for direct volume rendering has been shown to be an effective means of extracting materials and their boundaries for both scalar and multivariate data. The most common multi-dimensional transfer function consists of a two-dimensional (2D) histogram with axes representing a subset of the feature space (e.g., value vs. value gradient magnitude), with each...
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