Research on occlusion face recognition based on deep networks

Abstract

Based on the spread of the new crown epidemic, the use of masks has been popularized, so it has a significant impact on the development of face recognition under the cover. The study of how to improve the performance of face recognition under occlusion conditions is also an important topic in the field of face recognition in the future. At the same time, the neural network model is one of the most important models in deep learning, in the field of image classification, face recognition based on deep network has also been proved to be an efficient feature extraction method, this paper divides the face recognition method based on occlusion into two categories: local feature class based on non-occlusion area and feature class based on recognition occlusion area; The basic processes of these two types of methods are summarized, and the specific cases of these two types of occlusion face recognition methods are analyzed. Further summarize the advantages and disadvantages of each and elaborate them. At the end of the article, the shortcomings and future development trends of the current shielding face recognition research are summarized.