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Attendance management is crucial for institutions and workplaces, yet many still rely on outdated methods.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