Abstract
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.
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Haag, M., Theilmann, W., Schäfer, K., Nagel, H.H. (1997). Integration of image sequence evaluation and fuzzy metric temporal logic programming. In: Brewka, G., Habel, C., Nebel, B. (eds) KI-97: Advances in Artificial Intelligence. KI 1997. Lecture Notes in Computer Science, vol 1303. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3540634932_24
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DOI: https://doi.org/10.1007/3540634932_24
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