Mateu Sbert: An Information Theory Framework for Viewpoint Selection and Mesh Saliency

Viewpoint selection is an emerging area in computer graphics with applications in fields such as scene exploration, image-based modeling, and volume visualization. Best view selection algorithms are used to obtain the minimum number of views in order to understand or model an object or scene better. In this talk, we present a unified framework for viewpoint selection and mesh saliency computation based on the definition of an information channel between a set of viewpoints (input) and the set of polygons of an object (output). The mutual information of this channel is shown to be a powerful tool to deal with viewpoint selection, viewpoint stability, object exploration, polygonal information and saliency. The information channel is also extended to deal with volume visualization. Finally, we present the application of viewpoint mutual information to mesh simplification.