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by Kniss, Kindlmann, Hansen University of Utah

Multi-Dimensional Transfer Functions for Interactive Volume Rendering & Interactive Volume Rendering Using Multi-Dimensional Transfer Functions, etc. by Kniss, Kindlmann, Hansen University of Utah. presentation by Nicholas Schwarz schwarz@evl.uic.edu Electronic Visualization Lab

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by Kniss, Kindlmann, Hansen University of Utah

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  1. Multi-Dimensional Transfer Functions for Interactive Volume Rendering & Interactive Volume Rendering Using Multi-Dimensional Transfer Functions, etc. by Kniss, Kindlmann, Hansen University of Utah presentation by Nicholas Schwarz schwarz@evl.uic.edu Electronic Visualization Lab University of Illinois at Chicago

  2. Introduction • Easy to find objects in spatial domain, but difficult to do so in transfer function domain. • Different regions may have same scalar value. • Enormous degrees of freedom. • Small changes in transfer function result in drastic/unexpected changes in the visualization.

  3. Multi-Dimensional Transfer Functions • Gradient – local rate of change (1st derivative)

  4. Multi-Dimensional Transfer Function • Hessian – second partial derivative

  5. Multivariate Data

  6. Hardware • Dependent texture reads: use color fragments to generate texture coordinates, replace those color fragments with corresponding entries from a texture. • Classification: can get vary large for multi-dimensions, so higher dimensions are limited. • Surface shading: cube map dependent texture reads – treat RGB component as a vector used as texture coordinates for a cub map. Bad for shading homogeneous regions, but good for boundaries.

  7. Hardware • Shadows: off screen render buffer to accumulate the amount of light.

  8. Nifty Widget

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