用人脸检测与识别技术实现教室自动点名，省时高效。
ClassVision: AI-Powered Classroom Attendance System
- 基于RetinaFace和人脸识别技术实现实时身份验证。
- 50x50像素裁剪嵌入效果最佳，准确率显著提升。
- 适合需要高效管理出勤的学校或企业培训场景。
学生与职场人士每日需完成考勤。传统纸质或在线签到方式依赖人工，耗时耗力。为解决人工考勤难题，本研究探索使用人脸检测（FD）与人脸识别（FR）技术自动化教育场景中的考勤流程，构建了ClassVision课程考勤系统。该系统具备人机交互友好、支持实时图像处理的网页界面，可自动识别课堂中学生身份并记录出勤。实验表明，RetinaFace作为最优人脸检测模型，配合人脸识别进行验证时，在50x50像素裁剪嵌入下表现最佳，具有较高准确性。
原文摘要 · Abstract (English)
Students and working professionals have to go through the attendance process every day. Traditional methods of marking attendance using pen and paper or online platforms are human-intensive and time-consuming. To address the challenges in manual attendance processes, this research explores the use of face detection (FD) and face recognition (FR) technology to automate the attendance process, particularly in educational settings, and build a ClassVision course attendance system. We also propose an automated attendance system featuring a human-computer interaction (HCI) and user-friendly web interface that utilizes real-time image processing to identify and recognize students in classrooms and automatically record their attendance. We identified RetinaFace as the best face detection model, and when combined with Face Recognition for verification, it provided the most promising results with a cropped embedding of 50x50 pixels.
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