A graphical simulator for modeling complex crowd behaviors

HAO, Yu, XU, Zhijie, LIU, Ying, WANG, Jing and FAN, Jiulun (2018). A graphical simulator for modeling complex crowd behaviors. In: 2018 22nd International Conference Information Visualisation. IEEE, 6-11.

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Abstract

Abnormal crowd behaviors of varied real-world settings could represent or pose serious threat to public safety. The video data required for relevant analysis are often difficult to acquire due to security, privacy and data protection issues. Without large amounts of realistic crowd data, it is difficult to develop and verify crowd behavioral models, event detection techniques, and corresponding test and evaluations. This paper presented a synthetic method for generating crowd movements and tendency based on existing social and behavioral studies. Graph and tree searching algorithms as well as game engine-enabled techniques have been adopted in the study. The main outcomes of this research include a categorization model for entity-based behaviors following a linear aggregation approach; and the construction of an innovative agent-based pipeline for the synthesis of A-Star path-finding algorithm and an enhanced Social Force Model. A Spatial-Temporal Texture (STT) technique has been adopted for the evaluation of the model's effectiveness. Tests have highlighted the visual similarities between STTs extracted from the simulations and their counterparts - video recordings - from the real-world.

Item Type:	Book Section
Additional Information:	22nd International Conference Information Visualisation, 10-13 July, 2018 Salerno, Italy. ISSN: 2375-0138
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018:	Faculty of Science, Technology and Arts > Department of Computing
Identification Number:	https://doi.org/10.1109/iV.2018.00012
Page Range:	6-11
Depositing User:	Jing Wang
Date Deposited:	23 Aug 2018 09:41
Last Modified:	17 Mar 2021 16:17
URI:	https://shura.shu.ac.uk/id/eprint/18880

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