Multi Face Detection Based Attendance System

Face recognition-based data driven solutions are used to solve many real-time problems in day-to-day life. At present some of the known methods like physical presence verification, Id card scanning system and single face system are used in attendance marking purpose. The existing system often focuses on single face detection which consumes more time. Moreover, they do not address the challenges like bulk entry of individuals at a point of time. This limitation hinders their effectiveness in scenarios where multiple faces need to be detected simultaneously in crowded entry and exits like hostels, library, and apartment and so on. This proposed system is designed to detect and track multiple faces simultaneously from the live video streams. Additionally, it includes a time stamping mechanism that records the exact time when each face is captured. Also, it records the unknown faces with entry and exit time details which helpful to trace the people at later point of time. The proposed solution is applied to track the movements in entry and exit points of the Hostel also supports to monitor the unauthorized movements inside the hostel. The unauthorized person movement records help to enhance their security. So, it eliminates the manual attendance marking and speed up the overall process. The proposed real-time multiple face detection system fills this gap by introducing advanced algorithms like haarcascade and innovative features.