Wolfgang Heidrich

Publications (4)0 Total impact

• Source

  Available from: Mateu Sbert

  Article: Automatic View Selection Using Viewpoint Entropy and its Applications to Image-based Modelling.

  Pere-Pau Vázquez, Miquel Feixas, Mateu Sbert, Wolfgang Heidrich
  Comput. Graph. Forum. 01/2003; 22:689-700.
• Article: Image-Based Modeling Using Viewpoint Entropy

  Pere-pau Vzquez, Miquel Feixast, Wolfgang Heidrich, Mateu Sbert
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  ABSTRACT: We present a new method to automatically determine the correct camera placement positions in order to obtain a minimal set of views for Image-Based Rendering. The viewpoints should cover all visible polygons with an adequate quality, so that we sample the polygons at enough rate. This allows to avoid the excessive redundancy of the data existing in several other approaches. The localisation of interesting viewpoints is performed with the aid of an information theory-based measure, dubbed viewpoint entropy. This measure can be used to determine the amount of information seen from a viewpoint. We have also developed a greedy algorithm that aims to miniraise the number of images needed to represent a scene.
  08/2002;
• Source

  Available from: Mateu Sbert

  Article: Viewpoint Selection using Viewpoint Entropy

  Pere-pau Vazquez, Miquel Feixas, Mateu Sbert, Wolfgang Heidrich
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  ABSTRACT: 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. 1
  10/2001;
• Source

  Available from: Mateu Sbert

  Article: Image-based modeling using viewpoint entropy

  Pere Pau Vazquez Alcocer, Miquel Feixas, Mateu Sbert Cassasayas, Wolfgang Heidrich
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  ABSTRACT: We present a new method to automatically determine the correct camera placement positions in order to obtain a minimal set of views for Image-Based Rendering. The viewpoints should cover all visible polygons with an adequate quality, so that we sample the polygons at enough rate. This allows to avoid the excessive redundancy of the data existing in several other approaches. The localisation of interesting viewpoints is performed with the aid on an information theory-based measure, dubbed viewpoint entropy. This measure can be used to determine the amount of information seen from a viewpoint. We have also developed a greedy algorithm that aims to minimise the number of images need to represent a scene. In contrast to other approaches, our system uses a special preprocess for textures to avoid artifacts appearing in partially occluded textured polygons. Therefore no visible detail of these images is lost. Postprint (author’s final draft)