BMVC 2004, Kingston, 7th-9th Sept, 2004

An Illumination Invariant Face Recognition System for Access Control using Video
O. Arandjelovic and R. Cipolla (University of Cambridge)

Illumination and pose invariance are the most challenging aspects of face recognition. In
this paper we describe a fully automatic face recognition system that uses video information
to achieve illumination and pose robustness. In the proposed method, highly nonlinear manifolds
of face motion are approximated using three Gaussian pose clusters. Pose robustness is
achieved by comparing the corresponding pose clusters and probabilistically combining the
results to derive a measure of similarity between two manifolds. Illumination is normalized
on a per-pose basis. Region-based gamma intensity correction is used to correct for coarse
illumination changes, while further refinement is achieved by combining a learnt linear manifold
of illumination variation with constraints on face pattern distribution, derived from
video. Comparative experimental evaluation is presented and the proposed method is shown
to greatly outperform state-of-the-art algorithms. Consistent recognition rates of 94-100%
are achieved across dramatic changes in illumination.
(pdf article)