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Representation of Behavioral Knowledge for Planning and Plan-Recognition in a Cognitive Vision System

  • Michael Arens
  • Hans-Hellmut Nagel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2479)

Abstract

The algorithmic generation of textual descriptions of image sequences requires conceptual knowledge. In our case, a stationary camera recorded image sequences of road traffic scenes. The necessary conceptual knowledge has been provided in the form of a so-called Situation Graph Tree (SGT). Other endeavors such as the generation of a synthetic image sequence from a textual description or the transformation of machine vision results for use in a driver assistance system could profit from the exploitation of the same conceptual knowledge, but more in a planning (pre-scriptive) rather than a de-scriptive context.

A recently discussed planning formalism, Hierarchical Task Networks (HTNs), exhibits a number of formal similarities with SGTs. These suggest to investigate whether and to which extent SGTs may be re-cast as HTNs in order to re-use the conceptual knowledge about the behavior of vehicles in road traffic scenes for planning purposes.

Keywords

Reduction Scheme Conceptual Knowledge Action Atom Driver Assistance System Task Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Michael Arens
    • 1
  • Hans-Hellmut Nagel
    • 1
  1. 1.Institut für Algorithmen und Kognitive SystemeFakultät für Informatik der Universität Karlsruhe (TH)KarlsruheGermany

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