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Title: Hierarchical Task Network planning with common-sense reasoning for multiple-people behaviour analysis
Authors: Santofimia, Maria J.
Martinez-del-Rincon, Jesus
Hong, Xin
Zhou, Huiyu
Miller, Paul
Villa, David
Lopez, Juan C.
First Published: 28-Sep-2016
Publisher: Elsevier for Pergamon
Citation: Expert Systems with Applications, 2017, 69, pp. 118-134 (17)
Abstract: Safety on public transport is a major concern for the relevant authorities. We address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.
DOI Link: 10.1016/j.eswa.2016.09.038
ISSN: 0957-4174
eISSN: 1873-6793
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2016, Elsevier for Pergamon. Deposited with reference to the publisher’s open access archiving policy.
Appears in Collections:Published Articles, Dept. of Computer Science

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