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URN: urn:nbn:de:0030-drops-16050
URL: http://drops.dagstuhl.de/opus/volltexte/2008/1605/

Neumann, Bernd

Bayesian Compositional Hierarchies - A Probabilistic Structure for Scene Interpretation

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Abstract

In high-level vision, it is often useful to organize conceptual models in compositional hierarchies. For example, models of building facades (which are used here as examples) can be described in terms of constituent parts such as balconies or window arrays which in turn may be further decomposed. While compositional hierarchies are widely used in scene interpretation, it is not clear how to model and exploit probabilistic dependencies which may exist within and between aggregates. In this contribution I present Bayesian Aggregate Hierarchies as a means to capture probabilistic dependencies in a compositional hierarchy. The formalism integrates well with object-centered representations and extends Bayesian Networks by allowing arbitrary probabilistic dependencies within aggregates. To obtain efficient inference procedures, the aggregate structure must possess abstraction properties which ensure that internal aggregate properties are only affected in accordance with the hierarchical structure. Using examples from the building domain, it is shown that probabilistic aggregate information can thus be integrated into a logic-based scene interpretation system and provide a preference measure for interpretation steps.

BibTeX - Entry

@InProceedings{neumann:DSP:2008:1605,
  author =	{Bernd Neumann},
  title =	{Bayesian Compositional Hierarchies - A Probabilistic Structure for Scene Interpretation},
  booktitle =	{Logic and Probability for Scene Interpretation },
  year =	{2008},
  editor =	{Anthony G. Cohn and David C. Hogg and Ralf M{\"o}ller and Bernd Neumann},
  number =	{08091},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2008/1605},
  annote =	{Keywords: Scene interpretation, compositional hierarchy, probabilistic inference}
}

Keywords: Scene interpretation, compositional hierarchy, probabilistic inference
Seminar: 08091 - Logic and Probability for Scene Interpretation
Issue date: 2008
Date of publication: 23.10.2008


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