A new look at filtering techniques for illumination invariance in automatic face recognition

Oggie Arandelovic*, Roberto Cipolla

*Corresponding author for this work

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

23 Citations (Scopus)

Abstract

Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we propose a novel, general recognition framework for efficient matching of individual face images, sets or sequences. The framework is based on simple image processing filters that compete with unprocessed greyscale input to yield a single matching score between individuals. It is shown how the discrepancy between illumination conditions between novel input and the training data set can be estimated and used to weigh the contribution of two competing representations. We describe an extensive empirical evaluation of the proposed method on 171 individuals and over 1300 video sequences with extreme illumination, pose and head motion variation. On this challenging data set our algorithm consistently demonstrated a dramatic performance improvement over traditional filtering approaches. We demonstrate a reduction of 50-75% in recognition error rates, the best performing method-filter combination correctly recognizing 96% of the individuals.

Original languageEnglish
Title of host publicationFGR 2006: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Pages449-454
Number of pages6
Volume2006
DOIs
Publication statusPublished - 2006
EventFGR 2006: 7th International Conference on Automatic Face and Gesture Recognition - Southampton, United Kingdom
Duration: 10 Apr 200612 Apr 2006

Conference

ConferenceFGR 2006: 7th International Conference on Automatic Face and Gesture Recognition
Country/TerritoryUnited Kingdom
CitySouthampton
Period10/04/0612/04/06

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