Gradient edge map features for frontal face recognition under extreme illumination changes

Oggie Arandelovic*

*Corresponding author for this work

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

38 Citations (Scopus)


Our aim in this paper is to robustly match frontal faces in the presence of extreme illumination changes, using only a single training image per person and a single probe image. In the illumination conditions we consider, which include those with the dominant light source placed behind and to the side of the user, directly above and pointing downwards or indeed below and pointing upwards, this is a most challenging problem. The presence of sharp cast shadows, large poorly illuminated regions of the face, quantum and quantization noise and other nuisance effects, makes it difficult to extract a sufficiently discriminative yet robust representation. We introduce a representation which is based on image gradient directions near robust edges which correspond to characteristic facial features. Robust edges are extracted using a cascade of processing steps, each of which seeks to harness further discriminative information or normalize for a particular source of extra-personal appearance variability. The proposed representation was evaluated on the extremely difficult YaleB data set. Unlike most of the previous work we include all available illuminations, perform training using a single image per person and match these also to a single probe image. In this challenging evaluation setup, the proposed gradient edge map achieved 0.8% error rate, demonstrating a nearly perfect receiver-operator characteristic curve behaviour. This is by far the best performance achieved in this setup reported in the literature, the best performing methods previously proposed attaining error rates of approximately 6-7%.

Original languageEnglish
Title of host publicationBMVC 2012 - Electronic Proceedings of the British Machine Vision Conference 2012
PublisherBritish Machine Vision Association, BMVA
Publication statusPublished - 2012
Event2012 23rd British Machine Vision Conference, BMVC 2012 - Guildford, Surrey, United Kingdom
Duration: 3 Sept 20127 Sept 2012


Conference2012 23rd British Machine Vision Conference, BMVC 2012
Country/TerritoryUnited Kingdom
CityGuildford, Surrey


Dive into the research topics of 'Gradient edge map features for frontal face recognition under extreme illumination changes'. Together they form a unique fingerprint.

Cite this