Demo Data from EDBT 2026 / reviewers in the wild / expert
David J. Muraki
dblp:52/4788
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Rendering · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Rendering
sampling and reconstruction |
0.1 | 1 | 2006 | A Spectral Analysis of Function Composition and its Implications for Sampling in Direct Volume Visualization · IEEE Trans. Vis. Comput. Graph. 2006 |
Rendering
volume rendering |
0.1 | 1 | 2006 | A Spectral Analysis of Function Composition and its Implications for Sampling in Direct Volume Visualization · IEEE Trans. Vis. Comput. Graph. 2006 |
Rendering › volume rendering
pre-integrated volume rendering |
0.0 | 1 | 2006 | A Spectral Analysis of Function Composition and its Implications for Sampling in Direct Volume Visualization · IEEE Trans. Vis. Comput. Graph. 2006 |
Methods — techniques the papers use, named apart from their topics
stationary phase method · 0.1spectral analysis · 0.1function composition analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | A Spectral Analysis of Function Composition and its Implications for Sampling in Direct Volume VisualizationabstractIn this paper we investigate the effects of function composition in the form g(f(x)) = h(x) by means of a spectral analysis of h. We decompose the spectral description of h(x) into a scalar product of the spectral description of g(x) and a term that solely depends on f(x) and that is independent of g(x). We then use the method of stationary phase to derive the essential maximum frequency of g(f(x)) bounding the main portion of the energy of its spectrum. This limit is the product of the maximum frequency of g(x) and the maximum derivative of f(x). This leads to a proper sampling of the composition h of the two functions g and f. We apply our theoretical results to a fundamental open problem in volume rendering-the proper sampling of the rendering integral after the application of a transfer function. In particular, we demonstrate how the sampling criterion can be incorporated in adaptive ray integration, visualization with multi-dimensional transfer functions, and pre-integrated volume rendering. Steven Bergner, Torsten Möller, Daniel Weiskopf, David J. Muraki |
IEEE Trans. Vis. Comput. Graph. | 4 |