Viewpoint Selection using Viewpoint Entropy

نویسندگان

  • Pere-Pau Vázquez
  • Miquel Feixas
  • Mateu Sbert
  • Wolfgang Heidrich
چکیده

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.

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تاریخ انتشار 2001