Face recognition from face motion manifolds using robust kernel resistor-average distance

Oggie Arandelovic, Roberto Cipolla

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

29 Citations (Scopus)

Abstract

In this work we consider face recognition from face motion manifolds. An information-theoretic approach with Resistor-Average Distance (RAD) as a dissimilarity measure between distributions of face images is proposed. We introduce a kernel-based algorithm that retains the simplicity of the closed-form expression for the RAD between two normal distributions, while allowing for modelling of complex, nonlinear manifolds. Additionally, it is shown how errors in the face registration process can be modelled to significantly improve recognition. Recognition performance of our method is experimentally demonstrated and shown to outperform state-of-the-art algorithms. Recognition rates of 97-100% are consistently achieved on databases of 35-90 people.

Original languageEnglish
Title of host publicationIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
PublisherIEEE Computer Society
Volume2004-January
EditionJanuary
DOIs
Publication statusPublished - 2004
Event2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2004 - Washington, United States
Duration: 27 Jun 20042 Jul 2004

Conference

Conference2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2004
Country/TerritoryUnited States
CityWashington
Period27/06/042/07/04

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