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Ubiquitous robotics in physical human action recognition: A comparison between dynamic ANNs and GP

Theodoridis, T and Agapitos, A and Hu, O and Lucas, SM (2008) Ubiquitous robotics in physical human action recognition: A comparison between dynamic ANNs and GP. In: UNSPECIFIED, ? - ?.

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Abstract

Two different classifier representations based on dynamic Artificial Neural Networks (ANNs) and Genetic Programming (GP) are being compared on a human action recognition task by an ubiquitous mobile robot. The classification methodologies used, process time series generated by an indoor ubiquitous 3D tracker which generates spatial points based on 23 reflectable markers attached on a human body. This investigation focuses mainly on class discrimination of normal and aggressive action recognition performed by an architecture which implements an interconnection between an ubiquitous 3D sensory tracker system and a mobile robot to perceive, process, and classify physical human actions. The 3D tracker and the robot are used as a perception-to-action architecture to process physical activities generated by human subjects. Both classifiers process the activity time series to eventually generate surveillance assessment reports by generating evaluation statistics indicating the classification accuracy of the actions recognized. ©2008 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings - IEEE International Conference on Robotics and Automation
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: 03 Oct 2012 09:39
Last Modified: 23 Jan 2019 02:15
URI: http://repository.essex.ac.uk/id/eprint/4008

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