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Face set classification using maximally probable mutual modes

Arandjelovic, Ognjen and Cipolla, R. 2006, Face set classification using maximally probable mutual modes, in ICPR 2006 : Proceedings of the International Conference on Pattern Recognition 2006, IEEE, Piscataway, New Jersey, pp. 511-514, doi: 10.1109/ICPR.2006.535.

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Title Face set classification using maximally probable mutual modes
Author(s) Arandjelovic, Ognjen
Cipolla, R.
Conference name International Conference on Pattern Recognition (2006 : Hong Kong, China)
Conference location Hong Kong, China
Conference dates 20-24 Aug. 2006
Title of proceedings ICPR 2006 : Proceedings of the International Conference on Pattern Recognition 2006
Editor(s) [Unknown]
Publication date 2006
Conference series International Conference on Pattern Recognition
Start page 511
End page 514
Total pages 4
Publisher IEEE
Place of publication Piscataway, New Jersey
Summary In this paper we consider face recognition from sets of face images and, in particular, recognition invariance to illumination. The main contribution is an algorithm based on the novel concept of maximally probable mutual modes (MMPM). Specifically: (i) we discuss and derive a local manifold illumination invariant and (ii) show how the invariant naturally leads to a formulation of "common modes" of two face appearance distributions. Recognition is then performed by finding the most probable mode, which is shown to be an eigenvalue problem. The effectiveness of the proposed method is demonstrated empirically on a challenging database containing the total of 700 video sequences of 100 individuals
ISBN 0769525210
Language eng
DOI 10.1109/ICPR.2006.535
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 ©2006, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30058436

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.