Illumination compensation subspace based robust face recognition

How to deal with illumination variation is an important research topic of face recognition. In this paper, an illumination invariant face recognition strategy is put forward to deal with single gallery recognition. We give a proof that the illumination distinction among face images of s specific people could be linearly described through a carefully constructed subspace that is independent of both appearance and illumination, which is called the illumination compensation subspace. And then the subspace construction approach is introduced. Finally, a straightforward yet effective illumination compensation based face recognition algorithm is proposed which unifies both the calculation of illumination compensation and face recognition process into once l 1 optimization. In a word, our approach effectively reduces the influence of illumination diversity on face recognition accuracy without incurring evident increase in optimization complexity. The proposed method has been evaluated on the Extended Yale B dataset.