Face Recognition with Partial Occlusion

In the present paper, we propose a novel method for face recognition against contiguous occlusion. The general idea is to eliminate the impact of occlusions on the linear regression-based classification (LRC) method. Inspired by the level set methods that can provide smooth and closed contours as segmentation results which fit for the assumption of spatially continuity about occlusion, we show how to use the spatial continuity of pixels to segment the occluded regions. By incorporating the idea of level set based image segmentation into the LRC, the proposed approach is capable of reliably determining the occluded regions and removing them from LRC framework. Extensive experiments on publicly available databases (Extended Yale B and AR) show the efficacy of the proposed approach against different types of occlusion.