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Information Theory in Computer Graphics and Visualization by Mateu Sbert; Miquel Feixas; Ivan Viola; Jaume Rigau; Miguel Chover is a scholarly article available to read on EtoBox.

What is Information Theory in Computer Graphics and Visualization about?

We present various applications of information theory for computer graphics, based on the use of information measures such as entropy and mutual information. Some application areas are hierarchical radiosity, pixel supersampling, best view selection, scene exploration, ambient occlusion, mesh saliency, mesh simplification, and scientific visualization. Course Description We present a half-day course to review several applications of information theory for computer graphics and visualization. Information theory tools, widely used in scientific fields such as engineering, physics, genetics, neuroscience, are also emerging as useful transversal tools in computer graphics and related fields. We introduce the basic concepts of information theory and how they map into the application areas. Application areas in computer graphics are viewpoint selection, mesh saliency, scene exploration, ambient occlusion, geometry simplication, radiosity, adaptive raytracing and shape descriptors. Applications areas in visualization are view selection for volume data, flow visualization, ambient occlusion, time-varying volume visualization, transfer function definition, time-varying volume visualization,

Author

Mateu Sbert; Miquel Feixas; Ivan Viola; Jaume Rigau; Miguel Chover

Publisher

ACM

Published

2011

Language

EN