Htike, Kyaw Kyaw and Khalifa, Othman Omran and Mohd. Ramli, Huda Adibah and Abushariah, Mohammad A. M. (2014) Human activity recognition for video surveillance using sequences of postures. In: Third International Conference on e-Technologies and Networks for Development (ICeND2014), April 29 - May 1, 2014, Campus of Hadath, Beirut, Lebanon.
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Abstract
The Human activities recognition has become a research area of great interest as it has many potential applications; including automated surveillance, sign language interpretation and human-computer interfaces. In recent years, an extensive research has been conducted in this field. This paper presents a part of a novel a Human posture recognition system for video surveillance using one static camera. The training and testing stages were implemented using four different classifiers which are K Means, Fuzzy C Means, Multilayer Perceptron SelfOrganizing Maps and Feedforward Neural networks. The accuracy recognition of used classifiers is calculated. The results indicate that Self-Organizing Maps shows the highest recognition rate. Moreover, results show that supervised learning classifiers tend to perform better than unsupervised classifiers for the case of human posture recognition. Furthermore, for each individual classifier, the recognition rate has been found to be proportional to the number of training postures. Performance comparisons between the proposed system and existing similar systems were also shown.
Item Type: | Conference or Workshop Item (Plenary Papers) |
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Additional Information: | 4119/38609 |
Uncontrolled Keywords: | human posture, activity recognition, video sequences, intelligent systems, neural networks |
Subjects: | T Technology > T Technology (General) > T10.5 Communication of technical information |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering > Department of Electrical and Computer Engineering |
Depositing User: | Prof. Dr Othman O. Khalifa |
Date Deposited: | 09 Oct 2014 09:53 |
Last Modified: | 18 Sep 2017 10:02 |
URI: | http://irep.iium.edu.my/id/eprint/38609 |
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