Name
Abstract | ||
|---|---|---|
In this paper we present a new framework for the analysis of scene visibility and radiosity complexity We introduce a number of complexity measures from information theory quantifying how difficult it is to compute with accuracy the visibility and radiosity in a scene. We define the continuous mutual information as a complexity measure of a scene independent of whatever discretisation, and discrete mutual information as the complexity of a discretised scene. Mutual information can be understood as the degree of correlation ol dependence between all the points or patches of Scene. Thus, low complexity corresponds to low correlation and vice versa. Experiments illustrating that the best mesh of a given scene among a number of alternatives corresponds to the one with the highest discrete mutual information, indicate the feasibility of the approach. Unlike continuous mutual information, which is very cheap to compute, the computation of discrete mutual information can however be quite demanding. We will develop cheap complexity measure estimates and derive practical algorithms from this framework in future work. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1111/1467-8659.00331 | COMPUTER GRAPHICS FORUM |
Keywords | Field | DocType |
rendering, radiosity, Monte Carlo, information theory, entropy, mutual information | Information theory,Computer vision,Discretization,Visibility,Computer science,Theoretical computer science,Variation of information,Mutual information,Artificial intelligence,Radiosity (computer graphics),Rendering (computer graphics),Computation | Journal |
Volume | Issue | ISSN |
18 | 3 | 0167-7055 |
Citations | PageRank | References |
29 | 2.06 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miquel Feixas | 1 | 637 | 45.61 |
| Esteve del Acebo | 2 | 76 | 11.10 |
| Philippe Bekaert | 3 | 758 | 67.00 |
| Mateu Sbert | 4 | 1108 | 123.95 |