A Survey of Face Recognition Methods Based on Mask Region Restoration Algorithm

Abstract

The complex and diverse background conditions, the variability of human face and the artificial deliberate transformation have all become the problems that traditional face recognition technology can't solve, and they can't really reflect the imperceptible advantages of face recognition. After wearing masks, the most important mouth and nose areas of human face are covered by these masks with different shapes and colors, and some facial features are hidden, and the key feature points that can be extracted are greatly reduced. In this paper, the existing mask region repair algorithms at home and abroad are classified and summarized, mainly including mask occlusion face recognition based on robust occlusion, mask occlusion face recognition based on sparse representation classification and mask occlusion face recognition based on neural network. It is pointed out that partial occlusion is one of the main difficulties. The main methods and shortcomings of face recognition based on mask region repair algorithm are systematically analyzed and summarized, and the main problems and possible research ways in the future are analyzed.