An illumination invariant face recognition system for access control using video Arandjelovic, Ognjen and Cipolla, R. 2004, An illumination invariant face recognition system for access control using video, in BMVC 2004 : Proceedings of the British Machine Vision Conference, BMVA Press, Manchester, Eng., pp. 537-546, doi: 10.5244/C.18.56. Attached Files Name Description MIMEType Size Downloads arandjelovic-illuminationinvariant-2004.pdf Published version application/pdf 332.98KB 257 Title An illumination invariant face recognition system for access control using video Author(s) Arandjelovic, Ognjen Cipolla, R. Conference name British Machine Vision. Conference (2004 : London, England) Conference location London, England Conference dates 7-9 Sept. 2004 Title of proceedings BMVC 2004 : Proceedings of the British Machine Vision Conference Editor(s) Hoppe, A. Barman, S. Ellis, T. Publication date 2004 Conference series British Machine Vision Conference Start page 537 End page 546 Total pages 10 Publisher BMVA Press Place of publication Manchester, Eng. Summary Illumination and pose invariance are the most challenging aspects of face recognition. In this paper we describe a fully automatic face recognition system that uses video information to achieve illumination and pose robustness. In the proposed method, highly nonlinear manifolds of face motion are approximated using three Gaussian pose clusters. Pose robustness is achieved by comparing the corresponding pose clusters and probabilistically combining the results to derive a measure of similarity between two manifolds. Illumination is normalized on a per-pose basis. Region-based gamma intensity correction is used to correct for coarse illumination changes, while further refinement is achieved by combining a learnt linear manifold of illumination variation with constraints on face pattern distribution, derived from video. Comparative experimental evaluation is presented and the proposed method is shown to greatly outperform state-of-the-art algorithms. Consistent recognition rates of 94-100% are achieved across dramatic changes in illumination. ISBN 01901725241 Language eng DOI 10.5244/C.18.56 Field of Research 080104 Computer Vision 080106 Image Processing 080109 Pattern Recognition and Data Mining Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture) HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2004, BMVA Press Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30058461 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment Centre for Pattern Recognition and Data Analytics (PRADA) 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 Tue, 26 Nov 2013, 14:17:09 EST Tue, 26 Nov 2013, 14:22:52 EST Fri, 24 Jan 2014, 10:24:14 EST Tue, 17 Nov 2015, 13:59:48 EST Tue, 05 Dec 2017, 12:44:58 EST Fri, 07 Sep 2018, 16:48:43 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 251 Abstract Views, 257 File Downloads  -  Detailed Statistics Created: Tue, 26 Nov 2013, 14:17:09 EST