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.08091.14
URN: urn:nbn:de:0030-drops-16165
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1616/
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Hummel, Britta ; Thiemann, Werner ; Lulcheva, Irina

Scene Understanding of Urban Road Intersections with Description Logic

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08091.HummelBritta.Paper.1616.pdf (0.3 MB)

Abstract

Road recognition from video sequences has been solved robustly only for small, often simplified subsets of possible road configurations. A massive augmentation of the amount of prior knowledge may pave the way towards a generation of estimators of more general applicability. This contribution introduces Description Logic extended by rules as a promising knowledge representation formalism for road and intersection understanding.
We have set up a Description Logic knowledge base for arbitrary road and intersection geometries and configurations. Logically stated geometric constraints and road building regulations constrain the hypothesis space. Sensor data from an in-vehicle vision sensor and from a digital map provide evidence for a particular intersection. Partial observability and different abstraction layers of the input data are naturally handled by the representation formalism.
Deductive inference services – namely satisfiability, classification, entailment, and consistency – are then used to narrow down the intersection hypothesis space based on the evidence and the background knowledge, and to retrieve intersection information relevant to a user, i.e. a human or a driver assistance system. We conclude with an outlook towards non-deductive reasoning, namely model construction under the answer set semantics.

BibTeX - Entry

@InProceedings{hummel_et_al:DagSemProc.08091.14,
  author =	{Hummel, Britta and Thiemann, Werner and Lulcheva, Irina},
  title =	{{Scene Understanding of Urban Road Intersections with Description Logic}},
  booktitle =	{Logic and Probability for Scene Interpretation},
  pages =	{1--16},
  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/2008/1616},
  URN =		{urn:nbn:de:0030-drops-16165},
  doi =		{10.4230/DagSemProc.08091.14},
  annote =	{Keywords: Autonomous Driving;, Road Recognition, Knowledge Representation, Description Logic, Nonmonotonic Reasoning}
}

Keywords: Autonomous Driving;, Road Recognition, Knowledge Representation, Description Logic, Nonmonotonic Reasoning
Collection: 08091 - Logic and Probability for Scene Interpretation
Issue Date: 2008
Date of publication: 23.10.2008

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