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Efficient tensor based face recognition

Rana, Santu, Liu, Wanquan, Lazarescu, Mihai and Venkatesh, Svetha 2008, Efficient tensor based face recognition, in ICPR 2008 : Proceedings of the 19th International Conference on Pattern Recognition, IEEE, Washington, D. C., pp. 1-4, doi: 10.1109/ICPR.2008.4761706.

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Title Efficient tensor based face recognition
Author(s) Rana, SantuORCID iD for Rana, Santu orcid.org/0000-0003-2247-850X
Liu, Wanquan
Lazarescu, Mihai
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name International Conference on Pattern Recognition (19th : 2008 : Tampa, Fla.)
Conference location Tampa, Fla.
Conference dates 8-11 Dec. 2008
Title of proceedings ICPR 2008 : Proceedings of the 19th International Conference on Pattern Recognition
Editor(s) [Unknown]
Publication date 2008
Conference series International Conference on Pattern Recognition
Start page 1
End page 4
Total pages 4
Publisher IEEE
Place of publication Washington, D. C.
Keyword(s) Australia
computational efficiency
face recognition
image databases
image recognition
image reconstruction
performance evaluation
principal component analysis
tensile stress
testing
Summary This paper addresses the limitation of current multilinear PCA based techniques, in terms of pro- hibitive computational cost of testing and poor gen- eralisation in some scenarios, when applied to large training databases. We define person-specific eigen-modes to obtain a set of projection bases, wherein a particular basis captures variation across light- ings and viewpoints for a particular person. A new recognition approach is developed utilizing these bases. The proposed approach performs on a par with the existing multilinear approaches, whilst sig- nificantly reducing the complexity order of the testing algorithm.
ISBN 1424421748
9781424421749
ISSN 1051-4651
Language eng
DOI 10.1109/ICPR.2008.4761706
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2008, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044585

Document type: Conference Paper
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.