Partially occluded face completion and recognition

Yue Deng, Dong Li, Xudong Xie, Kin-Man Lam, Qionghai Dai

Abstract: This paper proposes a spectral graph based algorithm for face image repairing, which can improve the recognition performance on occluded faces. Our algorithm is called `guided label-learning', so named from graphical models, and can achieve a high-quality repairing of damaged or occluded faces. We apply our face repairing algorithm in order to produce completed faces, and then use face recognition to evaluate the performance of our algorithm. Experiment results show that, at most, a nearly 30%-increase in the recognition rate can be achieved for occluded faces with the use of our algorithm.