HIERARCHICAL TASK NETWORK PLANNING WITH COMMON-SENSE REASONING FOR MULTIPLE-PEOPLE BEHAVIOUR ANALYSIS

Overall view of the process of sensed information understanding

 

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 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. 

Event association process

 

Experiments

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.

Metric 1. Sensor association accuracy
Metric 2. Atomic event association accuracy
Metric 3. Composite event association accuracy
Metric 4. Story recognition accuracy

 

Average accuracy rate
Full system accuracy rates obtained for each sequence and metric

 

Citation

Hierarchical Task Network Planning with Common-Sense Reasoning for Multiple-People Behaviour Analysis

M.J.Santofimia, J Martinez Del Rincon, X. Hong, H. Zhou, P Miller, D. Villa, J.C. Lopez

Expert Systems and applications, 2016.

  

bibtex
@article{Snatofimia2107,
title = "Hierarchical Task Network Planning with Common-Sense Reasoning for Multiple-People Behaviour Analysis",
author = "M.J. Santofimia and  J. Martinez del Rincon and X. Hong and H. Zhou and P. Miller and D. Villa and J.C Lopez",
year = "2016",
journal = "Expert Systems with Applications",

}