Structure learning for activity recognition in robot assisted intelligent environments

Authors:
Douglas G. McIlwraith;Julien Pansiot;James Ballantyne;Salman Valibeik;Ahmed Elsaify;Guang-Zhong Yang
Affiliations:
Royal Society/Wolfson MIC Laboratory, Dept. of Computing, Imperial College London, UK;Royal Society/Wolfson MIC Laboratory, Dept. of Computing and the Institute of Biomedical Engineering, Imperial College London, UK;Imperial College London, UK;Royal Society/Wolfson MIC Laboratory, Dept. of Computing and the Institute of Biomedical Engineering, Imperial College London, UK;Royal Society/Wolfson MIC Laboratory, Dept. of Computing, Imperial College London, UK;Royal Society/Wolfson MIC Laboratory, Dept. of Computing and the Institute of Biomedical Engineering, Imperial College London, UK
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

This paper presents a novel structure learning algorithm for the creation of distributed Bayesian networks over static and mobile Vision Sensor Network (VSN) nodes. These compose an assistive, intelligent environment for activity recognition. We provide results demonstrating a higher level of accuracy in the recognition of fine motor tasks when the environment is augmented with a mobile robot and show the ability of our learning algorithm to reduce VSN communication compared to a naïve, greedy structure learning technique.