Hidden Markov model for human to computer interaction: A study on human hand gesture recognition

Hidden Markov model for human to computer interaction: A study on human hand gesture recognition

Human hand recognition plays an important role in a wide range of applications ranging from sign language translators, gesture recognition, augmented reality, surveillance and medical image processing to various Human Computer Interaction (HCI) domains. Human hand is a complex articulated object co...

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Main Authors: Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini, Shafie, Amir Akramin, Salami, Momoh Jimoh Emiyoka
Format: Article
Language:English
Published: SpringerLink 2013
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://irep.iium.edu.my/16246/
http://irep.iium.edu.my/16246/
http://irep.iium.edu.my/16246/
http://irep.iium.edu.my/16246/1/10.1007_s10462-011-9292-0.pdf
id iium-16246
recordtype eprints
spelling iium-162462014-02-14T01:56:36Z http://irep.iium.edu.my/16246/ Hidden Markov model for human to computer interaction: A study on human hand gesture recognition Bilal, Sara Mohammed Osman Saleh Akmeliawati, Rini Shafie, Amir Akramin Salami, Momoh Jimoh Emiyoka TK Electrical engineering. Electronics Nuclear engineering Human hand recognition plays an important role in a wide range of applications ranging from sign language translators, gesture recognition, augmented reality, surveillance and medical image processing to various Human Computer Interaction (HCI) domains. Human hand is a complex articulated object consisting of many connected parts and joints. Therefore, for applications that involve HCI one can find many challenges to establish a system with high detection and recognition accuracy for hand posture and/or gesture. Hand posture is defined as a static hand configuration without any movement involved. Meanwhile, hand gesture is a sequence of hand postures connected by continuous motions. During the past decades, many approaches have been presented for hand posture and/or gesture recognition. In this paper, we provide a survey on approaches which are based on Hidden Markov Models (HMM) for hand posture and gesture recognition for HCI applications. SpringerLink 2013 Article PeerReviewed application/pdf en http://irep.iium.edu.my/16246/1/10.1007_s10462-011-9292-0.pdf Bilal, Sara Mohammed Osman Saleh and Akmeliawati, Rini and Shafie, Amir Akramin and Salami, Momoh Jimoh Emiyoka (2013) Hidden Markov model for human to computer interaction: A study on human hand gesture recognition. Artificial Intelligence Review, 40 (4). pp. 495-516. ISSN 0269-2821 http://dx.doi.org/10.1007/s10462-011-9292-0 doi:10.1007/s10462-011-9292-0
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Bilal, Sara Mohammed Osman Saleh
Akmeliawati, Rini
Shafie, Amir Akramin
Salami, Momoh Jimoh Emiyoka
Hidden Markov model for human to computer interaction: A study on human hand gesture recognition
description Human hand recognition plays an important role in a wide range of applications ranging from sign language translators, gesture recognition, augmented reality, surveillance and medical image processing to various Human Computer Interaction (HCI) domains. Human hand is a complex articulated object consisting of many connected parts and joints. Therefore, for applications that involve HCI one can find many challenges to establish a system with high detection and recognition accuracy for hand posture and/or gesture. Hand posture is defined as a static hand configuration without any movement involved. Meanwhile, hand gesture is a sequence of hand postures connected by continuous motions. During the past decades, many approaches have been presented for hand posture and/or gesture recognition. In this paper, we provide a survey on approaches which are based on Hidden Markov Models (HMM) for hand posture and gesture recognition for HCI applications.
format Article
author Bilal, Sara Mohammed Osman Saleh
Akmeliawati, Rini
Shafie, Amir Akramin
Salami, Momoh Jimoh Emiyoka
author_facet Bilal, Sara Mohammed Osman Saleh
Akmeliawati, Rini
Shafie, Amir Akramin
Salami, Momoh Jimoh Emiyoka
author_sort Bilal, Sara Mohammed Osman Saleh
title Hidden Markov model for human to computer interaction: A study on human hand gesture recognition
title_short Hidden Markov model for human to computer interaction: A study on human hand gesture recognition
title_full Hidden Markov model for human to computer interaction: A study on human hand gesture recognition
title_fullStr Hidden Markov model for human to computer interaction: A study on human hand gesture recognition
title_full_unstemmed Hidden Markov model for human to computer interaction: A study on human hand gesture recognition
title_sort hidden markov model for human to computer interaction: a study on human hand gesture recognition
publisher SpringerLink
publishDate 2013
url http://irep.iium.edu.my/16246/
http://irep.iium.edu.my/16246/
http://irep.iium.edu.my/16246/
http://irep.iium.edu.my/16246/1/10.1007_s10462-011-9292-0.pdf
first_indexed 2023-09-18T20:25:08Z
last_indexed 2023-09-18T20:25:08Z
_version_ 1777408365592313856

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