2D face analysis techniques, such as face landmarking, face recognition and
face verification, are reasonably dependent on illumination conditions which
are usually uncontrolled and unpredictable in the real world. An illumination
robust preprocessing method thus remains a significant challenge in reliable
face analysis. In this paper we propose a novel approach for improving lighting
normalization through building the underlying reflectance model which
characterizes interactions between skin surface, lighting source and camera
sensor, and elaborates the formation of face color appearance. Specifically,
the proposed illumination processing pipeline enables the generation of
Chromaticity Intrinsic Image (CII) in a log chromaticity space which is robust
to illumination variations. Moreover, as an advantage over most prevailing
methods, a photo-realistic color face image is subsequently reconstructed which
eliminates a wide variety of shadows whilst retaining the color information and
identity details. Experimental results under different scenarios and using
various face databases show the effectiveness of the proposed approach to deal
with lighting variations, including both soft and hard shadows, in face
recognition.

本文提出了一种新的方法来提高照明归一化的性能，通过建立反射模型和制定面部颜色外观的形成，生成了一种在对数颜色空间中稳健抵御照明变化的色度内在图像（CII）并在此基础上重新构建出逼真的面部彩色图像，实验结果表明该方法能够处理包括软阴影和硬阴影在内的照明变化，从而提高人脸识别的效果。