Locality preserving projections plus affinity propagation: A fast method for face recognition

Du, C; Yang, J; Wu, Q; Zhang, T; Yu, S

Locality preserving projections plus affinity propagation: A fast method for face recognition

Du, C Yang, J Wu, Q

Zhang, T Yu, S

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Publication Type:: Journal Article
Citation:: Optical Engineering, 2008, 47 (4)
Issue Date:: 2008-05-06

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Field	Value	Language
dc.contributor.author	Du, C	en_US
dc.contributor.author	Yang, J	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	Zhang, T	en_US
dc.contributor.author	Yu, S	en_US
dc.date.issued	2008-05-06	en_US
dc.identifier.citation	Optical Engineering, 2008, 47 (4)	en_US
dc.identifier.issn	0091-3286	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9235
dc.description.abstract	This letter develops a novel and fast framework called APLPP to tackle the face recognition task by combining locality preserving projections (LPP) with the affinity propagation clustering method. Unlike LPP, which uses all training images to identify a test image, our affinity propagation LPP (APLPP) uses much fewer Images, free of noise, for identification. Thus APLPP is more computationally efficient than LPP. Comparative experiments also indicate that APLPP outperforms LPP regarding the recognition rate. © 2008 Society of Photo-Optical Instrumentation Engineers.	en_US
dc.relation.ispartof	Optical Engineering	en_US
dc.relation.isbasedon	10.1117/1.2903838	en_US
dc.subject.classification	Optics	en_US
dc.title	Locality preserving projections plus affinity propagation: A fast method for face recognition	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	47	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0205 Optical Physics	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
dc.location.activity	ISI:000256242200002	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 - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	open_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	47	en_US

Abstract:

This letter develops a novel and fast framework called APLPP to tackle the face recognition task by combining locality preserving projections (LPP) with the affinity propagation clustering method. Unlike LPP, which uses all training images to identify a test image, our affinity propagation LPP (APLPP) uses much fewer Images, free of noise, for identification. Thus APLPP is more computationally efficient than LPP. Comparative experiments also indicate that APLPP outperforms LPP regarding the recognition rate. © 2008 Society of Photo-Optical Instrumentation Engineers.

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http://hdl.handle.net/10453/9235