Real Time Face Recognition System with Deep Residual Network and KNN

Human Face Recognition is the technique to determine the individuals using facial images. In this recent era, human face recognition will be effective to improve security issues. In this research area has a plentiful applications such as biometric, traffic control, information security, law application, digital identification, surveillance system. In this paper, our aim is to consider live streaming on surveillance system to detect human face from real time video feed to improve security issues in university area. Here, we used facial measurements known as embedding's calculation from faces and a network architecture named deep residual network is used with classification model KNN (k nearest neighboring). After this study, we found 91.05% accuracy.