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Learning and manipulating human's fingertip bending data for sign language translation using PCA-BMU classifier

Adnan, Nazrul H. and Wan, Khairunizam and AB, Shahriman and Abu Bakar, Juliana Aida and Aziz, Azri A. and Ali, M. Hazwan (2013) Learning and manipulating human's fingertip bending data for sign language translation using PCA-BMU classifier. CREAM : Current Research in Malaysia (Penyelidikan Terkini di Malaysia), 3. pp. 361-372. ISSN 2231-8305

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Nowadays the classification of fingers movement could be used to classify or categorize many kinds of human finger motions including the classification of sign language for verbal communication.Principal Component Analysis (PCA) is one of classical method that capable to be verity the finger motions for various alphabets by reducing the dimensional dataset of finger movements.The objective of this paper is to analyze the human finger motions / movements between thumbs,index and middle fingers while bending the fingers using PCA-BMU based techniques. The used of low cost DataGlove “GloveMAP” which is based on fingers adapted postural movement (or EigenFingers) of the principal component was applied in order to translate the finger bending to the sign language alphabets. Preliminary experimental results have shown that the “GloveMAP” DataGlove capable to measure several human Degree of Freedom (DoF), by “translating” them into a virtual commands for the interaction in the virtual world.

Item Type: Article
Uncontrolled Keywords: EigenFingers; finger movement classification; hand finger bending; Human-Computer Interaction; Principle Component Analysis (PCA)
Subjects: L Education > LB Theory and practice of education
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: College of Arts and Sciences
Depositing User: Mrs. Juliana Aida Abu Bakar
Date Deposited: 21 Apr 2014 05:04
Last Modified: 21 Apr 2014 05:04
URI: http://repo.uum.edu.my/id/eprint/10666

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