Real-Time Face Recognition Attendance System Based on Video Processing

The advent of big data and the commercial value of facial recognition technology have created a bright future for the technology, with a large market potential. This article proposes a face recognition participation framework based on continuous video processing. The article explores four aspects of the framework: the accuracy of facial recognition in offline recordings, the accuracy of facial recognition in continuous video processing, the dropout rate of the face recognition participation framework with continuous video processing, and the interface settings of the face recognition participation framework with continuous video processing. By analyzing these aspects, the article proposes a framework for participation based on facial recognition technology and conducts research on the framework with continuous video processing. Experimental results show that the accuracy of the video facial recognition framework can reach 82%. Compared with the traditional registration method, the face recognition participation framework can reduce the dropout rate by more than 60%. The dropout rate of missing classes has also been significantly reduced, which can effectively address the problems of students missing classes and leaving classes early.