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Face Recognition from Video Using the Generic Shape-Illumination Manifold

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conference contribution
posted on 2006-01-01, 00:00 authored by Ognjen Arandjelovic, R Cipolla
In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical applications. The objective of this work is to recognize faces using video sequences both for training and recognition input, in a realistic, unconstrained setup in which lighting, pose and user motion pattern have a wide variability and face images are of low resolution. In particular there are three areas of novelty: (i) we show how a photometric model of image formation can be combined with a statistical model of generic face appearance variation, learnt offline, to generalize in the presence of extreme illumination changes; (ii) we use the smoothness of geodesically local appearance manifold structure and a robust same-identity likelihood to achieve invariance to unseen head poses; and (iii) we introduce an accurate video sequence “reillumination” algorithm to achieve robustness to face motion patterns in video. We describe a fully automatic recognition system based on the proposed method and an extensive evaluation on 171 individuals and over 1300 video sequences with extreme illumination, pose and head motion variation. On this challenging data set our system consistently demonstrated a nearly perfect recognition rate (over 99.7%), significantly outperforming state-of-the-art commercial software and methods from the literature

History

Pagination

27 - 40

Location

Graz, Austria

Open access

  • Yes

Start date

2006-05-07

End date

2006-05-13

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2006, Springer

Editor/Contributor(s)

A Leonardis, H Bischof, A Pinz

Title of proceedings

ECCV 2006 : Proceedings of the 9th European Conference on Computer Vision 2006

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