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Modeling and Recognition of Video Events with Fuzzy Semantic Petri Nets

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Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 364))

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Abstract

This paper addresses the problem of modeling and automated recognition of video events. We propose to use Linear Temporal Logic as a language for events specification and Fuzzy Semantic Petri Nets (FSPN) as a tool for their recognition. FSPN are Petri nets coupled with an underlying fuzzy ontology. The ontology stores assertions (facts) concerning classification of objects and detected relations. Fuzzy predicates querying the ontology content are used as guards of transitions in FSPN. Tokens carry information on objects participating in a scenario and are equipped with weights indicating likelihood of their assignment to places. In turn, the places correspond to scenario steps. We describe a prototype detection system consisting of an FSPN interpreter, the fuzzy ontology, and a set of predicate evaluators. Initial tests yielding promising results are reported.

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Acknowledgments

This work is supported from AGH University of Science and Technology under Grant No. 11.11.120.859.

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Correspondence to Piotr Szwed .

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Szwed, P. (2016). Modeling and Recognition of Video Events with Fuzzy Semantic Petri Nets. In: Skulimowski, A., Kacprzyk, J. (eds) Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions. Advances in Intelligent Systems and Computing, vol 364. Springer, Cham. https://doi.org/10.1007/978-3-319-19090-7_38

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  • DOI: https://doi.org/10.1007/978-3-319-19090-7_38

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-19090-7

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