Accurate and efficient face recognition from video

Oggie Arandelovic*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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).

Original languageEnglish
Title of host publicationBritish Machine Vision Conference, BMVC 2010 - Proceedings
PublisherBritish Machine Vision Association, BMVA
Publication statusPublished - 2010
Event2010 21st British Machine Vision Conference, BMVC 2010 - Aberystwyth, United Kingdom
Duration: 31 Aug 20103 Sept 2010


Conference2010 21st British Machine Vision Conference, BMVC 2010
Country/TerritoryUnited Kingdom


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