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. Attached Files Name Description MIMEType Size Downloads venkatesh-efficienttensor-2008.pdf Published version application/pdf 146.72KB 160 Title Efficient tensor based face recognition Author(s) Rana, Santu orcid.org/0000-0003-2247-850X Liu, Wanquan Lazarescu, Mihai 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 Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30044585 Document type: Conference Paper Collections: School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. 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. Versions Version Filter Type Fri, 20 Apr 2012, 11:33:48 EST Fri, 27 Apr 2012, 10:47:44 EST Fri, 27 Apr 2012, 10:49:00 EST Thu, 03 May 2012, 10:05:05 EST Thu, 03 May 2012, 10:07:01 EST Wed, 06 Aug 2014, 15:27:42 EST Tue, 06 Sep 2016, 18:44:18 EST Thu, 01 Jun 2017, 15:47:46 EST Wed, 06 Dec 2017, 10:39:38 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 350 Abstract Views, 157 File Downloads  -  Detailed Statistics Created: Fri, 20 Apr 2012, 11:33:48 EST

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