Attendance-System-Face-Recognition

This project is a POC web application demonstrating the use of facial recognition for marking attendance built as a part of my PS -1 internship at ViitorCloud Technologies, Ahmedabad. It is a web application that can be used by the company to manage attendance of its employees.

Functionality Supported

• Admin and Employee Login
• Admin : Register new employees.
• Admin : Add employee photos to the training dataset.
• Admin: Train the model.
• Admin: View attendance reports of all employees. Attendance can be filtered by date or employee.
• Employee - View attendance reports of self.

Built Using

• OpenCV - Open Source Computer Vision and Machine Learning software library
• Dlib - C++ Library containing Machine Learning Algorithms
• face_recognition by Adam Geitgey
• Django- Python framework for web development.

Face Detection

• Dlib's HOG facial detector.

Facial Landmark Detection

• Dlib's 68 point shape predictor

Extraction of Facial Embeddings

• face_recognition by Adam Geitgey

Classification of Unknown Embedding

• using a Linear SVM (scikit-learn)

The application was tested on data from 25 employees at ViitorCloud Technologies, Ahmedabad.

Authors

1. Prathma Chowksey
2. Pratyush Goel
3. Shrey Shah

• Link to presentation
• Link to report