C029

FACE RECOGNITION ATTENDANCE TRACKING

MR. LEE ZHENG YANG, DR. WEE YIT YIN

AFFILIATION
Faculty of Information Science & Technology, Multimedia University

Description of Invention

This project introduces a real-time Face Recognition Attendance Tracking system that automates attendance using AI-powered facial recognition. It employs liveness detection, motion tracking, and anti-spoofing to ensure secure and accurate identity verification. Built with Python, Django, and deep learning models like ArcFace and MiniFASNetV2, the system captures faces via webcam and logs attendance automatically. An admin interface enables user and subject management. Designed for scalability and reliability, this system reduces manual errors, prevents proxy attendance, and is suitable for educational and corporate use