Human gait recognition and classification using similarity index for various conditions

Gait recognition is usually referred to signify the human identification by the style/way people walk in image sequences. Our aim is to implement the traditional gait recognition algorithm and to show the variation in gait recognition when subject is observed parallel to camera under three condition...

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Main Authors: Makhdoomi, Nahid A., Gunawan, Teddy Surya, Habaebi, Mohamed Hadi
Format: Article
Language:English
Published: IOP Publishing 2013
Subjects:
Online Access:http://irep.iium.edu.my/33973/
http://irep.iium.edu.my/33973/
http://irep.iium.edu.my/33973/
http://irep.iium.edu.my/33973/1/1757-899X_53_1_012069.pdf
id iium-33973
recordtype eprints
spelling iium-339732015-04-28T01:26:50Z http://irep.iium.edu.my/33973/ Human gait recognition and classification using similarity index for various conditions Makhdoomi, Nahid A. Gunawan, Teddy Surya Habaebi, Mohamed Hadi TK5101 Telecommunication. Including telegraphy, radio, radar, television Gait recognition is usually referred to signify the human identification by the style/way people walk in image sequences. Our aim is to implement the traditional gait recognition algorithm and to show the variation in gait recognition when subject is observed parallel to camera under three conditions- walking normal, carrying a bag and wearing a coat. However in this case, the work devises a novel method for the purpose of similarity computation rather than the traditional recognition where the overall recognition rate of 78.57 percent was obtained. IOP Publishing 2013-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/33973/1/1757-899X_53_1_012069.pdf Makhdoomi, Nahid A. and Gunawan, Teddy Surya and Habaebi, Mohamed Hadi (2013) Human gait recognition and classification using similarity index for various conditions. IOP Conference Series: Materials Science and Engineering, 53 (Conf.1). 012069-1. ISSN 1757-8981 http://iopscience.iop.org/1757-899X/53/1/012069 10.1088/1757-899X/53/1/012069
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TK5101 Telecommunication. Including telegraphy, radio, radar, television
spellingShingle TK5101 Telecommunication. Including telegraphy, radio, radar, television
Makhdoomi, Nahid A.
Gunawan, Teddy Surya
Habaebi, Mohamed Hadi
Human gait recognition and classification using similarity index for various conditions
description Gait recognition is usually referred to signify the human identification by the style/way people walk in image sequences. Our aim is to implement the traditional gait recognition algorithm and to show the variation in gait recognition when subject is observed parallel to camera under three conditions- walking normal, carrying a bag and wearing a coat. However in this case, the work devises a novel method for the purpose of similarity computation rather than the traditional recognition where the overall recognition rate of 78.57 percent was obtained.
format Article
author Makhdoomi, Nahid A.
Gunawan, Teddy Surya
Habaebi, Mohamed Hadi
author_facet Makhdoomi, Nahid A.
Gunawan, Teddy Surya
Habaebi, Mohamed Hadi
author_sort Makhdoomi, Nahid A.
title Human gait recognition and classification using similarity index for various conditions
title_short Human gait recognition and classification using similarity index for various conditions
title_full Human gait recognition and classification using similarity index for various conditions
title_fullStr Human gait recognition and classification using similarity index for various conditions
title_full_unstemmed Human gait recognition and classification using similarity index for various conditions
title_sort human gait recognition and classification using similarity index for various conditions
publisher IOP Publishing
publishDate 2013
url http://irep.iium.edu.my/33973/
http://irep.iium.edu.my/33973/
http://irep.iium.edu.my/33973/
http://irep.iium.edu.my/33973/1/1757-899X_53_1_012069.pdf
first_indexed 2023-09-18T20:49:02Z
last_indexed 2023-09-18T20:49:02Z
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