Clustering techniques for human posture recognition: K-Means, FCM and SOM

Kiran, Maleeha and Lai, Weng Kin and Kyaw Kyaw, Hitke Ali (2009) Clustering techniques for human posture recognition: K-Means, FCM and SOM. In: 9th WSEAS international conference on signal, speech and image processing, and 9th WSEAS international conference on Multimedia, internet & video technologies, 3 - 5 September, 2009, Budapest Tech, Hungary.

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Abstract

An automated surveillance system should have the ability to recognize human behaviour and to warn security personnel of any impending suspicious activity. Human posture is one of the key aspects of analyzing human behaviour. We investigated three clustering techniques to recognize human posture. The system is first trained to recognize a pair of posture and this is repeated for three pairs of human posture. Finally the system is trained to recognize five postures together. The clustering techniques used for the purpose of our investigation included K-Means, fuzzy C-Means and Self-Organizing Maps. The results showed that K-Means and Fuzzy C-Means performed well for the three pair of posture data. However these clustering techniques gave low accuracy when we scale up the dataset to five different postures. Self- Organizing Maps produce better recognition accuracy when tested for five postures.

Item Type:	Conference or Workshop Item (Full Paper)
Additional Information:	/1337 (Proceedings of the 9th WSEAS international conference on signal, speech and image processing, and 9th WSEAS international conference on Multimedia, internet & video technologies, ISBN: 9789604741144)
Uncontrolled Keywords:	Surveillance systems, posture recognition, Clustering, K-Means, fuzzy C-Means, Self-Organizing Maps
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	Ms Zati Atiqah Mohamad Tanuri
Date Deposited:	09 Aug 2011 12:21
Last Modified:	20 Dec 2011 08:11
URI:	http://irep.iium.edu.my/id/eprint/1337

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