Integration of image sequence evaluation and fuzzy metric temporal logic programming

  • M. Haag
  • W. Theilmann
  • K. Schäfer
  • H. -H. Nagel
Computer Perception / Neural Nets
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1303)


Advanced image sequence evaluation systems generate a voluminous amount of quantitative data which is increasingly difficult to assess. The challenge consists in abstracting from and reasoning with these data in order to create a more intuitive access to image evaluation results.

This contribution reports about experiences and results gained by connecting an existing advanced image sequence evaluation system with a Fuzzy Metric Temporal Logic (FMTL) system which is able to represent and process uncertain, time-related data. We will explain and demonstrate the advantage of using FMTL in order to automatically analyze traffic situations recorded by a video camera and evaluated by our image evaluation system. In particular, we shall address difficulties arising from feeding a logic inference system with uncertain real world data.


Computer Vision Knowledge Representation Fuzzy Sets Temporal Reasoning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • M. Haag
    • 1
  • W. Theilmann
    • 1
  • K. Schäfer
    • 1
  • H. -H. Nagel
    • 1
    • 2
  1. 1.Fakultät für Informatik der Universität Karlsruhe (THKarlsruheGermany
  2. 2.Karlsruhe Fraunhofer-Institut für Informations- und Datenverarbeitung (IITB)Karlsruhe

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