Local Gabor Binary Patterns Based on Kullback-Leibler Divergence for Partially Occluded Face Recognition

Wenchao Zhang, Shiguang Shan, Xilin Chen, Wen Gao

Abstract: The partial occlusion is one of the key issues in the face recognition community. To resolve the problem of partial occlusion, based on our previous work of local Gabor binary patterns (LGBP) for face recognition, we further propose Kullback-Leibler divergence (KLD)-based LGBP for partial occluded face recognition. The local property of LGBP face recognition is thoroughly used in the method, by introducing KLD between the LGBP feature of the local region and that of the non-occluded local region to estimate the probability of occlusion. The probability is used as the weight of the local region for the final feature matching. The experimental results on the AR face database demonstrate the effectiveness of the KLD-based LGBP face recognition method for partially occluded face images.