Face Recognition

Project: Face Recognition System for Live and Stored Media

Description: Built a face recognition application capable of identifying individuals from both live camera feeds and pre-recorded videos. Initially developed as a general recognition system, the project evolved to include features such as automated attendance tracking and peer-to-peer (P2P) camera-based monitoring for specific persons.

Key Features:

• Real-time face recognition using webcam or IP camera
• Recognition from stored video files and frame sequences
• Attendance logging based on recognized faces
• P2P monitoring for alerts when specific individuals appear
• Face data training and management system

Technologies & Tools Used:

• OpenCV
• face_recognition (dlib)
• Python

Use Case: Designed as a flexible solution for both offline and real-time face recognition, this project was adapted for real-world applications such as automated attendance and custom surveillance monitoring for target individuals.