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Mechanical feature attributes for modeling and pattern classification of physical activities

Theodoridis, T and Agapitos, A and Hu, H and Lucas, SM (2009) Mechanical feature attributes for modeling and pattern classification of physical activities. In: UNSPECIFIED, ? - ?.

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Abstract

A rigorous investigation on the synergy of mechanical attributes to engineer tactics for measuring human activity in terms of forces, as well as to provide independency and discrimination clarity of action recognition using linear and non-linear classification methodologies from data mining and evolutionary computation, are the main objectives where this paper focuses on. Mechanical analysis is employed to mathematically describe and model human movement by using a number of mechanical features inspired mainly from Kinematics Dynamics. Such features employ a twofold role on the descriptive analysis of an activity, initially to provide statistics regarding inertial expressions, probable hazard levels, body-status of energy loss, and finally to exploit these attributes by decomposing the 3D time series data for pattern recognition in terms of actions and behaviours. The performance statistics are being utilized by a mobile robot for remote surveillance within a smart environment. © 2009 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2009 IEEE International Conference on Information and Automation, ICIA 2009
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 11 Oct 2012 21:15
Last Modified: 17 Aug 2017 18:07
URI: http://repository.essex.ac.uk/id/eprint/4051

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