A trend for face recognition

He, X; Wu, Q; Zhang, H; Hintz, T

A trend for face recognition

He, X

Wu, Q

Zhang, H Hintz, T

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Publication Type:: Conference Proceeding
Citation:: Fourth International Conference on Information Technology and Applications, ICITA 2007, 2007, pp. 254 - 257
Issue Date:: 2007-12-03

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Field	Value	Language
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	Zhang, H	en_US
dc.contributor.author	Hintz, T	en_US
dc.date.issued	2007-12-03	en_US
dc.identifier.citation	Fourth International Conference on Information Technology and Applications, ICITA 2007, 2007, pp. 254 - 257	en_US
dc.identifier.isbn	0980326702	en_US
dc.identifier.isbn	9780980326703	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10788
dc.description.abstract	Face recognition has many applications in law enforcement, crowd surveillance, security access control and human computer interaction. However, the applications have been, greatly constrained by the limitations of the currently available recognition tools because these tools are either too slow, sensitive to pose, illumination and facial expression, or too expensive, and hence are impractical. Face recognition is difficult and still has a long way to go before it really becomes practical. The aim of this paper is to present how a system for real-time, robust and inexpensive face recognition may be approached. The system contains the following components: Low cost CCTV video cameras or simple digital, cameras to quickly locate faces on 2D face images captured. A constructor of 3D face images using the captured 2D images. Algorithms that accurately match the constructed 3D face images to the 2D face images preciously existing in a gallery in real-time for pose and illumination invariant face recognition.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0451666
dc.relation.ispartof	Fourth International Conference on Information Technology and Applications, ICITA 2007	en_US
dc.title	A trend for face recognition	en_US
dc.type	Conference Proceeding
utslib.for	1702 Cognitive Sciences	en_US
dc.location.activity	Harbin, China	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
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Face recognition has many applications in law enforcement, crowd surveillance, security access control and human computer interaction. However, the applications have been, greatly constrained by the limitations of the currently available recognition tools because these tools are either too slow, sensitive to pose, illumination and facial expression, or too expensive, and hence are impractical. Face recognition is difficult and still has a long way to go before it really becomes practical. The aim of this paper is to present how a system for real-time, robust and inexpensive face recognition may be approached. The system contains the following components: Low cost CCTV video cameras or simple digital, cameras to quickly locate faces on 2D face images captured. A constructor of 3D face images using the captured 2D images. Algorithms that accurately match the constructed 3D face images to the 2D face images preciously existing in a gallery in real-time for pose and illumination invariant face recognition.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/10788