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Accurate and efficient face recognition from video

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conference contribution
posted on 2010-01-01, 00:00 authored by Ognjen Arandjelovic
As a problem of high practical appeal but outstanding challenges, computer-based face recognition remains a topic of extensive research attention. In this paper we are specifically interested in the task of identifying a person from multiple training and query images. Thus, a novel method is proposed which advances the state-of-the-art in set based face recognition. Our method is based on a previously described invariant in the form of generic shape-illumination effects. The contributions include: (i) an analysis of computational demands of the original method and a demonstration of its practical limitations, (ii) a novel representation of personal appearance in the form of linked mixture models in image and pose-signature spaces, and (iii) an efficient (in terms of storage needs and matching time) manifold re-illumination algorithm based on the aforementioned representation. An evaluation and comparison of the proposed method with the original generic shape-illumination algorithm shows that comparably high recognition rates are achieved on a large data set (1.5% error on 700 face sets containing 100 individuals and extreme illumination variation) with a dramatic improvement in matching speed (over 700 times for sets containing 1600 faces) and storage requirements (independent of the number of training images).

History

Event

British Machine Vision Conference (21st : 2010 : Aberystwyth, Wales)

Pagination

1 - 10

Publisher

BMVA Press

Location

Aberystwyth, Wales

Place of publication

Manchester, England

Start date

2010-08-31

End date

2010-09-03

ISBN-10

1901725405

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2010, BMVA Press

Title of proceedings

BMVC 2010 : Proceedings of the 21st British machine vision association conference 2010

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