Pose and illumination compensation for 3D face recognition

The paper describes a face recognition system using a combination of color and depth images. To cope with illumination and pose variations 3D information is used for the normalization of the input images. The proposed pose compensation algorithm is based on a robust 3D face detection and pose estimation technique, while illumination compensation exploits depth data to recover the illumination of the scene and relight the image under frontal lighting. When normalized images, depicting upright orientation and frontal lighting, are used for classification significantly high recognition rates are achieved, as demonstrated on a face database with more than 2000 images.