Crowd Motion Pattern Detection at the Microscopic Level

In this paper we present a common-sense reasoning model for crowd motion pattern detection and behaviour analysis at the microscopic level. Information about the trajectories of individuals is represented with fuzzy predicates. The characteristic motion patterns and the behaviour of groups of indivi...

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Bibliographic Details
Published in2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) pp. 1093 - 1098
Main Authors Marcetic, Darijan, Males, Lada, Ribaric, Slobodan
Format Conference Proceeding
LanguageEnglish
Published Croatian Society MIPRO 01.05.2019
Subjects
Cognition
commonsense reasoning
Computational modeling
Computer vision
crowd
Estimation
fuzzy logic
Microscopy
motion pattern
Tracking
Trajectory
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Summary:In this paper we present a common-sense reasoning model for crowd motion pattern detection and behaviour analysis at the microscopic level. Information about the trajectories of individuals is represented with fuzzy predicates. The characteristic motion patterns and the behaviour of groups of individuals are described with fuzzy predicates and fuzzy functions, respectively. The usability of the proposed model is tested on a simulated crowd scenario. The obtained results show that the model supports the efficient representation of expert knowledge and detection of motion/behaviour patterns. The main contribution of this paper is a proposed model for motion pattern detection and classification based on fuzzy knowledge which can imitate common-sense reasoning.
ISSN:2623-8764
DOI:10.23919/MIPRO.2019.8756660