dc.contributor.author | Feixas, Miquel | en_US |
dc.contributor.author | Acebo, Esteve del | en_US |
dc.contributor.author | Bekaert, Philippe | en_US |
dc.contributor.author | Sbert, Mateu | en_US |
dc.contributor.editor | Dani Lischinski and Greg Ward Larson | en_US |
dc.date.accessioned | 2014-01-27T13:43:49Z | |
dc.date.available | 2014-01-27T13:43:49Z | |
dc.date.issued | 1999 | en_US |
dc.identifier.isbn | 3-211-83382-X | en_US |
dc.identifier.issn | 1727-3463 | en_US |
dc.identifier.uri | http://dx.doi.org/10.2312/EGWR/EGWR99/095-106 | en_US |
dc.description.abstract | Finding an optimal discretization of a scene is an important but difficult problem in radiosity. The efficiency of hierarchical radiosity for instance, depends entirely on the subdivision criterion and strategy that is used. We study the problem of adaptive scene discretization from the point of view of information theory. In previous work, we have introduced the concept of mutual information, which represents the information transfer or correlation in a scene, as a complexity measure and presented some intuitive arguments and preliminary results concerning the relation between mutual information and scene discretization. In this paper, we present a more general treatment supporting and extending our previous findings to the level that the development of practical information theory-based tools for optimal scene discretization becomes feasible. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.title | Information Theory Tools for Scene Discretization | en_US |
dc.description.seriesinformation | Eurographics Workshop on Rendering | en_US |