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:
Online Access: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
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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
building IIUM Repository
collection Online Access
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.
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institution International Islamic University Malaysia
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language English
English
last_indexed 2025-11-14T14:32:39Z
publishDate 2011
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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
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
title 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_short Gaussian Process Dynamical Models for Hand Gesture Interpretation in Sign Language
title_sort gaussian process dynamical models for hand gesture interpretation in sign language
topic TK Electrical engineering. Electronics Nuclear engineering
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