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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/20230

Title: Gesture recognition based on the probability distribution of arm trajectories
Authors: Wan Khairunizam, Wan Ahmad, Dr.
Hideyuki, Sawada
???metadata.dc.contributor.url???: khairunizam@unimap.edu.my
Keywords: Upper body motion;Arm trajectory;Fuzzy technique;Gesture recognition
Issue Date: Sep-2009
Publisher: The Society of Instrument and Control Engineers
Citation: Journal of Control, Measurement, and System Integration, vol. 2 (5), 2009, pages 263–270
Abstract: The use of human motions for the interaction between humans and computers is becoming an attractive alternative to verbal media, especially through the visual interpretation of the human body motion. In particular, hand gestures are used as non-verbal media for the humans to communicate with machines that pertain to the use of the human gestures to interact with them. This paper introduces a 3D motion measurement of the human upper body for the purpose of the gesture recognition, which is based on the probability distribution of arm trajectories. In this study, by examining the characteristics of the arm trajectories given by a signer, motion features are selected and classified by using a fuzzy technique. Experimental results show that the use of the features extracted from arm trajectories effectively works on the recognition of dynamic gestures of a human, and gives a good performance to classify various gesture patterns.
Description: Link to publisher's homepage at http://www.sice.or.jp/
URI: https://www.jstage.jst.go.jp/article/jcmsi/2/5/2_5_263/_article
http://hdl.handle.net/123456789/20230
ISSN: 1882-4889
Appears in Collections:Wan Khairunizam Wan Ahmad, Dr.
School of Mechatronic Engineering (Articles)

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