Analysis on face recognition based on five different viewpoint of face images using MTCNN and FaceNet

Abstract

Despite signi cant recent achievements in the eld of face recognition, implementing proper face recognition system by training enough data is still a problem because not everyone has enough photos that we can use to train. The objective of this paper is to implement a proper face recognition system which can successfully recognize known and unknown person by feeding only ve phase images for each person into training dataset. In this eld, accuracy and speed of identi cation is the main issue. There are at least two reasons for the importance behind the research of face recognition which has recently received signi cant attention, especially during the past several years. The rst is the wide range of commercial and law enforcement applications, and the second is the availability of feasible technologies after 30 years of research. In this paper, we present a review of the most successful existing method FaceNet for face recognition technology and how we can use it successfully even though we don't have enough data to train and to encourage researchers to embark on this topic. A brief on general information on this topic is also included to compose an overall review. This review is written by investigating past and ongoing studies done by other researchers related to the same subject.