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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.

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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
Persistent URL http://hdl.handle.net/10536/DRO/DU:30058461

Document type: Conference Paper
Collections: Centre for Pattern Recognition and Data Analytics
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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.