Hierarchical Task Network planning with common-sense reasoning for multiple-people behaviour analysis

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Hierarchical Task Network planning with common-sense reasoning for multiple-people behaviour analysis

Computer Architecture and Networks Group, University of Castilla-La Mancha, Ciudad Real, Spain

mariajose.santofimia@uclm.es

Centre for Secure Information Technologies, School of EEECS, Queens University Belfast, United Kingdom

j.martinez-del-rincon@qub.ac.uk

Centre for Secure Information Technologies, School of EEECS, Queens University Belfast, BT3 9DT, UK

x.hong@qub.ac.uk

Centre for Secure Information Technologies, School of EEECS, Queens University Belfast, BT3 9DT, UK

h.zhou@ecit.qub.ac.uk

Centre for Secure Information Technologies, School of EEECS, Queens University Belfast, United Kingdom

p.miller@qub.ac.uk

Computer Architecture and Networks Group, University of Castilla-La Mancha, Ciudad Real, Spain

david.villa@uclm.es

Computer Architecture and Networks Group, University of Castilla-La Mancha, Ciudad Real, Spain

juancarlos.lopez@uclm.es

  • JOURNAL — Expert Systems with Applications

  • PAGES — 118-134

  • ISSN 0957-4174

  • VOLUME  69

  • PUBLISHER  Elsevier

  • YEAR  2017

Maria J. Santofimia, Jesus Martinez-del-Rincon, Xin Hong, Huiyu Zhou, Paul Miller, David Villa, Juan C. Lopez, Hierarchical Task Network planning with common-sense reasoning for multiple-people behaviour analysis, In Expert Systems with Applications, Volume 69, 2017, Pages 118-134.

@article{SANTOFIMIA2017118,
title = "Hierarchical Task Network planning with common-sense reasoning for multiple-people behaviour analysis",
journal = "Expert Systems with Applications",
volume = "69",
number = "Supplement C",
pages = "118 - 134",
year = "2017",
issn = "0957-4174",
doi = "https://doi.org/10.1016/j.eswa.2016.09.038",
url = "http://www.sciencedirect.com/science/article/pii/S095741741630522X",
author = "Maria J. Santofimia and Jesus Martinez-del-Rincon and Xin Hong and Huiyu Zhou and Paul Miller and David Villa and Juan C. Lopez",
keywords = "Activity recognition, Common-sense, Video analysis, Surveillance"
}

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.

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2019-01-17T10:49:51+00:00