Adaptive Multiple Experts System for personal identification using facial behaviour biometrics

Tsai, PC; Tran, TP; Hintz, TB; Jan, T

Adaptive Multiple Experts System for personal identification using facial behaviour biometrics

Tsai, PC Tran, TP Hintz, TB Jan, T

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Publisher:: IEEE Press
Publication Type:: Conference Proceeding
Citation:: IEEE International Workshop on Multimedia Signal Processing (IEEE-MMSP 2008), 2008, pp. 660 - 665
Issue Date:: 2008-01

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Field	Value	Language
dc.contributor.author	Tsai, PC	en_US
dc.contributor.author	Tran, TP	en_US
dc.contributor.author	Hintz, TB	en_US
dc.contributor.author	Jan, T	en_US
dc.contributor.editor	N/A	en_US
dc.date	2008-10-08	en_US
dc.date.issued	2008-01	en_US
dc.identifier.citation	IEEE International Workshop on Multimedia Signal Processing (IEEE-MMSP 2008), 2008, pp. 660 - 665	en_US
dc.identifier.isbn	978-1-4244-2294-4	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11204
dc.description.abstract	Physiological and/or behavioural characteristics of humans such as face, gait and/or voice have been used in biometric recognition technology. Apart from these characteristics (which have been reported in the literature), the hypothesis of this research was to investigate if facial behaviour could be used for human identification. We analysed and proposed a multiple experts system, called Adaptive Multiple Experts System (AMES), for validating our hypothesis and analysis. We used the Japanese Female Facial Expression (JAFFE) database as it provides the facial behaviour traits for data collection. The experimental results indicate that facial behaviours may provide information about individual difference and, thus may be used as another behavioural biometric.	en_US
dc.publisher	IEEE Press	en_US
dc.relation.ispartof	IEEE International Workshop on Multimedia Signal Processing (IEEE-MMSP 2008)	en_US
dc.relation.ispartof	International Workshop on Multimedia Signal Processing	en_US
dc.relation.isbasedon	10.1109/MMSP.2008.466515	en_US
dc.rights	© 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.title	Adaptive Multiple Experts System for personal identification using facial behaviour biometrics	en_US
dc.type	Conference Proceeding
utslib.location	Cairns, Qld, Australia	en_US
utslib.location.activity	Cairns, Qld, Australia	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Cairns, Qld, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	Cairns, Qld, Australia	en_US
pubs.start-date	2008-10-08	en_US

Abstract:

Physiological and/or behavioural characteristics of humans such as face, gait and/or voice have been used in biometric recognition technology. Apart from these characteristics (which have been reported in the literature), the hypothesis of this research was to investigate if facial behaviour could be used for human identification. We analysed and proposed a multiple experts system, called Adaptive Multiple Experts System (AMES), for validating our hypothesis and analysis. We used the Japanese Female Facial Expression (JAFFE) database as it provides the facial behaviour traits for data collection. The experimental results indicate that facial behaviours may provide information about individual difference and, thus may be used as another behavioural biometric.

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http://hdl.handle.net/10453/11204