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CVIP / AIMajor

AI-Based Attendance System using Face Recognition

Automated attendance system that detects and recognizes student faces from a camera feed and marks attendance.

Problem Statement

Manual attendance taking is time-consuming and prone to errors or proxies. The objective is to design an AI-based system that automatically marks attendance by recognizing student faces in a classroom.

Proposed Solution

  • Use OpenCV for face detection (Haar cascades or DNN-based).
  • Use deep learning-based face recognition (FaceNet, DeepFace, or similar library).
  • Maintain a database of enrolled students with face embeddings.
  • During class, capture frames from camera, detect faces, recognize ID and store timestamp.
  • Generate daily/weekly attendance reports.

Tech Stack

  • Python, OpenCV
  • Deep learning library (TensorFlow / PyTorch or ready-made face recognition library)
  • SQLite / MySQL / PostgreSQL for attendance logs
  • Optional: Web dashboard using Flask/Django/React

Expected Outcomes

  • Reduced manual effort.
  • Accurate, tamper-proof attendance.
  • Reports for faculty and administration.