Generating face images under multiple illuminations based on a single front-lighted sample without 3D models

In this paper, we propose a novel generative method which could generate images with different illuminations by using a single front-lighted sample. The generative method is based on the linear Lambertian property and requires a bootstrap set with multiple subjects and specific illuminations for each subject. During the generation process, we also propose a scale decomposition method to retain the identity details between the generated image and the original sample. Unlike most of the generative methods, the proposed method does NOT require the 3D model. On the other hand, the generative method is proved flexible to use because it could be implemented altogether with the existing preprocessing methods. Experiment on extended Yale B and FRGC 2.0 databases shows that the generated images could diversify the illuminations of the gallery set, thus improving the recognition performance¹.