Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)

<Previous Article In Volume
Next Article In Volume>

Real-Time Face Detection and Recognition for Secure Access Control Using Deep Learning

Authors
Jannatul Ferdous Esha1, Lamia Habib1, Sabrina Subah Nisa1, Abu Sayed Md. Mostafizur Rahaman2, *
1Department of Information and Communication Technology, Bangladesh University of Professionals, Dhaka, Bangladesh
2Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh
*Corresponding author. Email: asmmr@juniv.edu
Corresponding Author
Abu Sayed Md. Mostafizur Rahaman
Available Online 8 June 2026.
DOI
10.2991/978-94-6239-664-7_42How to use a DOI?
Keywords
Face Detection; Face Recognition; ArcFace Model; Realtime Security; Intruder Detection; Web-based Interface
Abstract

In both the real and virtual worlds, security is still a major concern. In order to improve access control in online meeting environments, this study suggests an effective virtual security solution that integrates face detection and recognition. The system uses the OpenCV module for face identification and the ArcFace model from the Insight-Face library with a CNN-based deep learning method for face detection. Real-time authentication via live webcam input is made possible by an intuitive web-based interface. In addition to maintaining distinct databases for authorized and illegal users, the system has an automated email warning system that notifies authorities when an intrusion is detected. The technology is appropriate for real-world security applications since experimental findings show great accuracy and dependability in real-time facial recognition.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)
Series
Advances in Intelligent Systems Research
Publication Date
8 June 2026
ISBN
978-94-6239-664-7
ISSN
1951-6851
DOI
10.2991/978-94-6239-664-7_42How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jannatul Ferdous Esha
AU  - Lamia Habib
AU  - Sabrina Subah Nisa
AU  - Abu Sayed Md. Mostafizur Rahaman
PY  - 2026
DA  - 2026/06/08
TI  - Real-Time Face Detection and Recognition for Secure Access Control Using Deep Learning
BT  - Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)
PB  - Atlantis Press
SP  - 608
EP  - 622
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-664-7_42
DO  - 10.2991/978-94-6239-664-7_42
ID  - Esha2026
ER  -