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Face the Future: Revolutionizing Attendance Management with Facial Recognition

Team Members:

  • Ashwinee Kr. Samdarshi
  • Ayush Gupta
  • Ayush Rastogi
  • Ayush Rathore
  • Manan Padsala
  • Sarthak Saxena

Introduction:

Attendance management is crucial for institutions and workplaces, yet many still rely on outdated methods. We aim to bridge this gap by leveraging facial recognition technology.

Motivation:

Despite technological advancements, traditional attendance methods persist. Our motivation is to integrate cutting-edge technology into practical attendance systems.

Challenges:

Insufficient data for conventional model training and ensuring accuracy, reliability, and data security were primary challenges.

Objectives:

  • Develop an attendance system using facial recognition.
  • Overcome limitations of traditional methods with innovative approaches.
  • Create a user-friendly system improving attendance management for all stakeholders.

Traditional Methods:

  • Manual Attendance Taking
  • Barcode/RFID Scanning
  • Biometric Recognition

Recent Techniques:

  • Deep Learning-Based Facial Recognition
  • One-Shot Learning Approaches

Working Principle:

  • Feature Extraction
  • Similarity Metric
  • Prototypical Networks
  • Fine-Tuning and Transfer Learning

Key Benefits:

  • Accurate recognition with minimal data.
  • Real-time processing for swift attendance marking.
  • Robustness against environmental variations.

Future Opportunities:

Continued machine learning enables adaptation and performance optimization, ensuring high accuracy and reliability in attendance tracking without periodic retraining