Abstract
Crowd behaviour understanding in computer science is a research discipline which has grown rapidly in recent years. Specifically, we are currently able to generate large and high-resolution observation data through crowd sensing in varieties of spatial environments. This has also given us the advantage to adopt computer vision methods for detecting human behaviour. In this study, we adopted statistical mechanics principles with analogies of entropy and kinetic energy in classical molecular gases to derive features which describe crowd motions. These are implicitly measured, as basis for understanding behaviour, using a holistic three-dimensional representation, of crowd features including structure, energy and translation. As a result, we measured those features using computer vision in the view of machine understanding crowd behaviour. Usual behaviour is established from our expected crowd motions in context of the specific recipient spaces of our experiments. The behaviour which does not fall within the expected usual behaviour measurement is considered as an unusual behaviour. This research work was initiated in 2013 under the eVACUATE project, while it is currently ongoing under the S4AllCities project since 2020.
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Acknowledgements
The authors are very grateful to all of the eVACUATE research partners, particularly Drs. Zlatko Zlatev, Gianluca Correndo and Lee Middleton, for their collaboration, while we initiated the research work at the University of Southampton. We are also thankful to Professor Nicola Bellomo for his important research discussions on the fundamental modelling of crowd when we initiated this research under the eVACUATE project in 2013. Our research work was partly supported by the European Commission, initially under H2020 Grant Number 313361 in the eVACUATE project (2013–2017) and more recently under H2020 Grant Number 883522 of the ongoing S4AllCities project (2020–2023).
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Sabeur, Z., Arbab-Zavar, B. (2021). Crowd Behaviour Understanding Using Computer Vision and Statistical Mechanics Principles. In: Bellomo, N., Gibelli, L. (eds) Crowd Dynamics, Volume 3. Modeling and Simulation in Science, Engineering and Technology. Birkhäuser, Cham. https://doi.org/10.1007/978-3-030-91646-6_3
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DOI: https://doi.org/10.1007/978-3-030-91646-6_3
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