Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language

Classifying human hand gestures in the context of a Sign Language has been historically dominated by Artificial Neural Networks and Hidden Markov Model with varying degrees of success. The main objective of this paper is to introduce Gaussian Process Dynamical Model as an alternative machine learnin...

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Main Authors:	Gamage, Nuwan, Chow, Kuang Ye, Akmeliawati, Rini, Demidenko, Serge
Format:	Article
Language:	English English
Published:	Elsevier 2011
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/6002/ http://irep.iium.edu.my/6002/ http://irep.iium.edu.my/6002/ http://irep.iium.edu.my/6002/1/S0167865511002662 http://irep.iium.edu.my/6002/2/1-s2.0-S0167865511002662-main.pdf

id	iium-6002
recordtype	eprints
spelling	iium-60022013-07-02T01:44:28Z http://irep.iium.edu.my/6002/ Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language Gamage, Nuwan Chow, Kuang Ye Akmeliawati, Rini Demidenko, Serge TK Electrical engineering. Electronics Nuclear engineering Classifying human hand gestures in the context of a Sign Language has been historically dominated by Artificial Neural Networks and Hidden Markov Model with varying degrees of success. The main objective of this paper is to introduce Gaussian Process Dynamical Model as an alternative machine learning method for hand gesture interpretation in Sign Language. In support of this proposition, the paper presents the experimental results for Gaussian Process Dynamical Model against a database of 66 hand gestures from the Malaysian Sign Language. Furthermore, the Gaussian Process Dynamical Model is tested against established Hidden Markov Model for a comparative evaluation. A discussion on why Gaussian Process Dynamical Model is superior over existing methods in Sign Language interpretation task is then presented. Elsevier 2011-09-06 Article PeerReviewed application/pdf en http://irep.iium.edu.my/6002/1/S0167865511002662 application/pdf en http://irep.iium.edu.my/6002/2/1-s2.0-S0167865511002662-main.pdf Gamage, Nuwan and Chow, Kuang Ye and Akmeliawati, Rini and Demidenko, Serge (2011) Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language. Pattern Recognition Letters, 32 (15). pp. 2009-2014. ISSN 01678655 http://www.journals.elsevier.com/pattern-recognition-letters/ DOI:10.1016/j.patrec.2011.08.015
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Gamage, Nuwan Chow, Kuang Ye Akmeliawati, Rini Demidenko, Serge Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language
description	Classifying human hand gestures in the context of a Sign Language has been historically dominated by Artificial Neural Networks and Hidden Markov Model with varying degrees of success. The main objective of this paper is to introduce Gaussian Process Dynamical Model as an alternative machine learning method for hand gesture interpretation in Sign Language. In support of this proposition, the paper presents the experimental results for Gaussian Process Dynamical Model against a database of 66 hand gestures from the Malaysian Sign Language. Furthermore, the Gaussian Process Dynamical Model is tested against established Hidden Markov Model for a comparative evaluation. A discussion on why Gaussian Process Dynamical Model is superior over existing methods in Sign Language interpretation task is then presented.
format	Article
author	Gamage, Nuwan Chow, Kuang Ye Akmeliawati, Rini Demidenko, Serge
author_facet	Gamage, Nuwan Chow, Kuang Ye Akmeliawati, Rini Demidenko, Serge
author_sort	Gamage, Nuwan
title	Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language
title_short	Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language
title_full	Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language
title_fullStr	Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language
title_full_unstemmed	Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language
title_sort	gaussian process dynamical models for hand gesture interpretation in sign language
publisher	Elsevier
publishDate	2011
url	http://irep.iium.edu.my/6002/ http://irep.iium.edu.my/6002/ http://irep.iium.edu.my/6002/ http://irep.iium.edu.my/6002/1/S0167865511002662 http://irep.iium.edu.my/6002/2/1-s2.0-S0167865511002662-main.pdf
first_indexed	2023-09-18T20:14:50Z
last_indexed	2023-09-18T20:14:50Z
_version_	1777407717727535104

Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language

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