The Research and Analysis of Different Face Recognition Algorithms

With the background of fast developing artificial intelligence and Internet technology, face recognition, one of the product technologies under the theory of machine learning, has become widely applied on safety tests, identity confirmation, public security photos, and access control system. Based on the trend of its development speed, this technology will have well developed circumstances and the field of application will expand. One of the most essential reasons why it has become so popular is that the algorithms used for face recognition are advanced. In this paper, the author mainly researches five algorithms to realize face recognition based on relevant literature. They are separately CNN, PCA, SVM, MTCNN, and Facenet. After comparison and analysis, it can be found that CNN is one of the most suitable algorithms to recognize human faces, and PCA and SVM have problems of calculating speed. The use of complex neural networks can intensify the accuracy of face recognition just like MTCNN and Facenet. If combining different algorithms together and using their advantages in face recognition in different steps, the prediction of the algorithms will be better.