In order to understand the attendance of students in the classroom quickly and accurately, this paper proposes a classroom face recognition check-in algorithm developed based on Python language and OpenCV library. The Video Capture function provided by OpenCV library is used to call the camera for image acquisition, and then the acquired image is preprocessed to realize face detection using Haar-like features, the LBPH algorithm is used to extract features from the face image, and a training model is obtained through feature training and stored in the database. After the check-in is initiated, the acquired images are preprocessed, face detection and feature extraction are performed, and they are compared with the model previously stored in the database. The experimental results show that the algorithm is able to efficiently and accurately realize classroom face recognition check-in while ensuring lower cost.
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Song et al. (2024) studied this question.
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