Automatic age estimation system for face images

Lin, CT; Li, DL; Lai, JH; Han, MF; Chang, JY

Automatic age estimation system for face images

Lin, CT

Li, DL Lai, JH Han, MF Chang, JY

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Publication Type:: Journal Article
Citation:: International Journal of Advanced Robotic Systems, 2012, 9
Issue Date:: 2012-11-28

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Field	Value	Language
dc.contributor.author	Lin, CT https://orcid.org/0000-0001-8371-8197	en_US
dc.contributor.author	Li, DL	en_US
dc.contributor.author	Lai, JH	en_US
dc.contributor.author	Han, MF	en_US
dc.contributor.author	Chang, JY	en_US
dc.date.issued	2012-11-28	en_US
dc.identifier.citation	International Journal of Advanced Robotic Systems, 2012, 9	en_US
dc.identifier.issn	1729-8806	en_US
dc.identifier.uri	http://hdl.handle.net/10453/115047
dc.description.abstract	Humans are the most important tracking objects in surveillance systems. However, human tracking is not enough to provide the required information for personalized recognition. In this paper, we present a novel and reliable framework for automatic age estimation based on computer vision. It exploits global face features based on the combination of Gabor wavelets and orthogonal locality preserving projections. In addition, the proposed system can extract face aging features automatically in real-time. This means that the proposed system has more potential in applications compared to other semi-automatic systems. The results obtained from this novel approach could provide clearer insight for operators in the field of age estimation to develop real-world applications. © 2012 Lin et al.	en_US
dc.relation.ispartof	International Journal of Advanced Robotic Systems	en_US
dc.relation.isbasedon	10.5772/52862	en_US
dc.subject.classification	Industrial Engineering & Automation	en_US
dc.title	Automatic age estimation system for face images	en_US
dc.type	Journal Article
utslib.citation.volume	9	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
utslib.for	17 Psychology and Cognitive Sciences	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 Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	9	en_US

Abstract:

Humans are the most important tracking objects in surveillance systems. However, human tracking is not enough to provide the required information for personalized recognition. In this paper, we present a novel and reliable framework for automatic age estimation based on computer vision. It exploits global face features based on the combination of Gabor wavelets and orthogonal locality preserving projections. In addition, the proposed system can extract face aging features automatically in real-time. This means that the proposed system has more potential in applications compared to other semi-automatic systems. The results obtained from this novel approach could provide clearer insight for operators in the field of age estimation to develop real-world applications. © 2012 Lin et al.

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http://hdl.handle.net/10453/115047