Illumination-normalized face recognition using Chromaticity Intrinsic Image

Abstract

Face recognition (FR) across illumination variations endeavors to alleviate the effect of illumination changes on human face, which remains a great challenge in reliable FR. Most prior studies focus on normalization of holistic lighting intensity while neglecting or simplifying the mechanism of image color formation. In contrast, we propose in this paper a novel approach for lighting robust FR through building the underlying reflectance model which characterizes the appearance of face surface. Specifically, the proposed illumination processing pipeline sheds light on interactions among face surface, lighting and camera, and enables generation of Chromaticity Intrinsic Image (CII) in a log space which is robust to illumination variations. Experimental results on CMU-PIE and ESRC face databases show the effectiveness of the proposed approach to deal with lighting variations in FR.