Facetrace Attendance
Year: 2025
Type: article
Abstract: It’s a system designed to introduce modernization in attendance management by using facial recognition. Existing attendance systems which include manual registers or RFID cards are highly erroneous, fraud-prone and inefficient. This project offers a contactless, automated, accurate attendance management. System created with the use of the Django framework is a scalable and flexible system that integrates cutting-edge facial recognition libraries like OpenCV or similar tools. The system captures a live video stream from a camera, detects them in the real-time work and matches them with the pre-registered database of users. Attendance of the person is automatically recorded in the DB once the match is confirmed. Source code of the project is modular and well-documented, it can be easily modified and extended by developers. The project presents real practical use of machine learning and AI principles in solving real-life tasks. It demonstrates how machine learning can be used in web technologies to increase the effectiveness and productivity of everyday activities.
Authors: Priyal Jain, Rajdeep Bhatia, Harjinder Singh Khalsa, Prof. Vivek Kumar Gupta, Prof. Manish Joshi
Institution: Medi-Caps University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409107278