Interaction analysis through fuzzy temporal logic: Extensions for clustering and parameter learning

Joris Ijsselmuiden, Johannes Dornheim

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

Interaction analysis is defined as the generation of semantic descriptions from machine perception. This can be achieved through a combination of fuzzy metric temporal logic (FMTL) and situation graph trees (SGTs). We extended the FMTL/SGT framework with modules for clustering and parameter learning and we showed their advantages. The contributions of this paper are 1) the combination of FMTL/SGT reasoning with a customized clustering algorithm, 2) a method for learning FMTL rule parameters, 3) a new FMTL/SGT model that implements some powerful fuzzy spatiotemporal concepts, and 4) evaluation of this system in a crisis response control room setting.

Original languageEnglish
Title of host publicationAVSS 2015 - 12th IEEE International Conference on Advanced Video and Signal Based Surveillance
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781467376327
DOIs
Publication statusPublished - 2015
Event12th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2015 - Karlsruhe, Germany
Duration: 25 Aug 201528 Aug 2015

Conference

Conference12th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2015
CountryGermany
CityKarlsruhe
Period25/08/1528/08/15

Keywords

  • Adaptation models
  • Clustering algorithms
  • Cognition
  • Measurement
  • Noise
  • Semantics
  • Spatiotemporal phenomena

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    Ijsselmuiden, J., & Dornheim, J. (2015). Interaction analysis through fuzzy temporal logic: Extensions for clustering and parameter learning. In AVSS 2015 - 12th IEEE International Conference on Advanced Video and Signal Based Surveillance [7301794] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AVSS.2015.7301794