License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.08091.10
URN: urn:nbn:de:0030-drops-16097
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1609/
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Wachsmuth, Sven ; Swadzba, Agnes

Probabilistic Scene Modeling for Situated Computer Vision

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08091.SwadzbaAgnes.Paper.1609.pdf (0.4 MB)

Abstract

Verbal statements and vision are a rich source of information
in a human-machine interaction scenario. For this reason Situated
Computer Vision aims to include knowledge about the communicative
situation in which it takes place. This paper presents three approaches
how to achieve scene models of such scenarios combining different modalities.
Seeing (planar) scenes as configurations of parts leads to a probabilistic
modeling with Bayes’ nets relating spoken utterances with results
of an object recognition step. In the second approach parallel datasets
form the basis for analyzing the statistical dependencies between them
through learning a statistical translation model which maps between
these datasets (here: words in a text and boundary fragments extracted
in 2D images). The third approach deals with complex indoor scenes from
which 3D data is acquired. Planar structures in the 3D points and statistics
extracted on these planar patches describe the coarse spatial layouts
of different indoor room types in such a way that a holistic classification
scheme can be provided.

BibTeX - Entry

@InProceedings{wachsmuth_et_al:DagSemProc.08091.10,
  author =	{Wachsmuth, Sven and Swadzba, Agnes},
  title =	{{Probabilistic Scene Modeling for Situated Computer Vision}},
  booktitle =	{Logic and Probability for Scene Interpretation},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8091},
  editor =	{Anthony G. Cohn and David C. Hogg and Ralf M\"{o}ller and Bernd Neumann},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2008/1609},
  URN =		{urn:nbn:de:0030-drops-16097},
  doi =		{10.4230/DagSemProc.08091.10},
  annote =	{Keywords: Scene Modeling, Human Robot Interaction}
}

Keywords: Scene Modeling, Human Robot Interaction
Collection: 08091 - Logic and Probability for Scene Interpretation
Issue Date: 2008
Date of publication: 23.10.2008

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