Human behavioural analysis with self-organizing map for ambient assisted living

Appiah, K. ORCID: 0000-0002-9480-0679, Hunter, A., Lotfi, A. ORCID: 0000-0002-5139-6565, Waltham, C. and Dickinson, P., 2014. Human behavioural analysis with self-organizing map for ambient assisted living. In: 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Beijing, China, 6.7.2014. IEEE, pp. 2430-2437. ISBN 9781479920730


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This paper presents a system for automatically classifying the resting location of a moving object in an indoor environment. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a low-cost, low-power automated home-based surveillance system, capable of monitoring activity level of elders living alone independently. The proposed system runs on an embedded platform with a specialised ceiling-mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels and to detect specific events such as potential falls. First order motion information, including first order moving average smoothing, is generated from the 2D image coordinates (trajectories). A novel edge-based object detection algorithm capable of running at a reasonable speed on the embedded platform has been developed. The classification is dynamic and achieved in real-time. The dynamic classifier is achieved using a SOFM and a probabilistic model. Experimental results show less than 20% classification error, showing the robustness of our approach over others in literature with minimal power consumption. The head location of the subject is also estimated by a novel approach capable of running on any resource limited platform with power constraints.

Item Type: Chapter in book
Creators: Appiah, K., Hunter, A., Lotfi, A., Waltham, C. and Dickinson, P.
Publisher: IEEE
Date: 2014
ISBN: 9781479920730
Divisions: Schools > School of Science and Technology
Record created by: EPrints Services
Date Added: 09 Oct 2015 09:42
Last Modified: 09 Jun 2017 13:09

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