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Computation of good viewpoints is important in several fields: computational geometry, visual servoing, robot motion, graph drawing, etc. In addition, selection of good views is rapidly becoming a key issue in computer graphics due to the new techniques
of Image Based Rendering. Although there
is no consensus about what a good view means in Computer Graphics, the quality of a viewpoint is intuitively related to how much information it gives us about a scene. In this paper we use the theoretical basis provided by Information Theory to define
a new measure, viewpoint entropy, that allows us to compute good viewing positions automatically. We also show how it can be used to select a set of N good views of a scene for scene understanding. Finally, we design an algorithm that uses this measure
to explore automatically objects or scenes.
CitationVázquez, P. [et al.]. Viewpoint selection using viewpoint entropy. A: International Fall Workshop on Vision, Modeling, and Visualization. "6th International Fall Workshop on Vision, Modeling, and Visualization". Stuttgart: 2001, p. 273-280.
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