RecogniMark: An Intelligent Attendance Management System Using Facial Recognition

Abstract: This work discusses the implementation and design of an Attendance Management System that uses facial recognition for automatic attendance marking. The system uses computer vision methods, such as OpenCV, Dlib, and the Face Recognition library, to identify and detect people based on face features. Implemented using Django for the backend and JavaScript for the frontend, the system provides secure face recognition in real-time, registration, and attendance logging. Facial embeddings are retained in a SQLite database, while images are stored in AWS S3 for safe cloud storage. The system also uses TensorFlow to examine attendance patterns, providing predictive insights into user behavior. The automated solution eliminates human error, provides accurate attendance records, and improves security. The proposed system is scalable, adaptable to various environments, and provides a robust alternative to traditional attendance methods in educational and organizational settings.