Name
Abstract | ||
|---|---|---|
Volume rendering is a flexible technique for visualizing dense 3D volumetric datasets. A central element of volume rendering is the conversion between data values and observable quantities such as color and opacity. This process is usually realized through the use of transfer functions that are precomputed and stored in lookup tables. For multidimensional transfer functions applied to multivariate data, these lookup tables become prohibitively large. We propose the direct evaluation of a particular type of transfer functions based on a sum of Gaussians. Because of their simple form (in terms of number of parameters), these functions and their analytic integrals along line segments can be evaluated efficiently on current graphics hardware, obviating the need for precomputed lookup tables. We have adopted these transfer functions because they are well suited for classification based on a unique combination of multiple data values that localize features in the transfer function domain. We apply this technique to the visualization of several multivariate datasets (CT, cryosection) that are difficult to classify and render accurately at interactive rates using traditional approaches. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/VISUAL.2003.1250412 | IEEE Visualization 2003 |
Keywords | Field | DocType |
multi-field volume,lookup table,gaussian transfer functions,flexible technique,multiple data value,multivariate datasets,transfer function,multidimensional transfer function,data value,transfer function domain,volume rendering,precomputed lookup table,cryosection,data visualisation,gaussian distribution,visualization,transfer functions,graphics hardware,ct,multivariate data | Computer vision,Lookup table,Line segment,Volume rendering,Data visualization,Graphics hardware,Visualization,Computer science,Theoretical computer science,Gaussian,Transfer function,Artificial intelligence | Conference |
ISBN | Citations | PageRank |
0-7695-2030-8 | 45 | 2.50 |
References | Authors | |
20 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joe Kniss | 1 | 1277 | 70.59 |
| Simon Premoze | 2 | 608 | 39.74 |
| Milan Ikits | 3 | 193 | 14.57 |
| Aaron Lefohn | 4 | 282 | 22.38 |
| Charles Hansen | 5 | 1574 | 95.02 |
| Emil Praun | 6 | 1333 | 74.82 |