Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/11261
Title: Vision-based hand gesture interaction using particle filter, principle component analysis and transition network
Authors: Wang, Z
Zhang, Z
Wang, F
Sun, Y
Keywords: Human computer interaction;Hand gesture recognition;Hand tracking;Principle component analysis;Particle filter
Issue Date: 2014
Publisher: Binary Information Press
Citation: Journal of Information and Computational Science, 11(4): 1037 - 1045, (2014)
Abstract: Vision-based human-computer interaction is becoming important nowadays. It offers natural interaction with computers and frees users from mechanical interaction devices, which is favourable especially for wearable computers. This paper presents a human-computer interaction system based on a conventional webcam and hand gesture recognition. This interaction system works in real time and enables users to control a computer cursor with hand motions and gestures instead of a mouse. Five hand gestures are designed on behalf of five mouse operations: moving, left click, left-double click, right click and no-action. An algorithm based on Particle Filter is used for tracking the hand position. PCA-based feature selection is used for recognizing the hand gestures. A transition network is also employed for improving the accuracy and reliability of the interaction system. This interaction system shows good performance in the recognition and interaction test.
URI: http://www.joics.com/publishedpapers.aspx
http://bura.brunel.ac.uk/handle/2438/11261
DOI: http://dx.doi.org/10.12733/jics20102890
ISSN: 1548-7741
Appears in Collections:Dept of Computer Science Research Papers

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