Deep Learning based Multi-face Recognition System for Automatic Attendance Registering in Classrooms

Aaditya Prabal Chawla; S. Ebenezer Juliet; Ankur Suman; Aqif Khan; G. Manikandan

doi:10.2991/978-94-6463-740-3_18

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Deep Learning based Multi-face Recognition System for Automatic Attendance Registering in Classrooms

Authors

Aaditya Prabal Chawla¹, S. Ebenezer Juliet²^{, *}, Ankur Suman³, Aqif Khan⁴, G. Manikandan⁵

¹School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India

²Associate Professor Sr, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India

³School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India

⁴School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India

⁵Assistant Professor Sr. Grade 1, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India

^*Corresponding author. Email: ebenezer.juliet@vit.ac.in

Corresponding Author

S. Ebenezer Juliet

Available Online 25 June 2025.

DOI: 10.2991/978-94-6463-740-3_18 How to use a DOI?
Keywords: Multi-Face Recognition; Deep Learning; MTCNN; FaceNet; Attendance system
Abstract: Multi-face recognition remains an active area in deep learning domain, excelled by the need for enhanced security and efficiency in various applications. The motivation for proposing this automatic multi-face recognition system originates from the increasing demand for non-intrusive and reliable identification methods in educational institutions to automate the attendance process in classrooms and seminar halls. The proposed system focuses on multi-face detection and multi-face recognition in live class photos and videos using Multi-Task Cascaded Convolutional Networks (MTCNN) and FaceNet respectively. The custom dataset has been prepared and face augmentation is done on custom dataset to improve the recognition rate of pretrained FaceNet model. This CNN based deep neural network model is designed to deploy a multi-face recognition system which is capable of detecting and recognizing the student faces in live classroom environment. The system is tested with variations in poses, expressions, lighting effects, and occlusion by ensuring high reliability in various conditions. The benefits of the proposed system are, it automates the attendance process in educational settings, thereby eliminating the manual entry. The proposed system is implemented in real-life conditions which will automatically recognize students’ faces and mark their attendance in classrooms. Finally, this work provides the directions to improve further the robustness and accuracy of the multi-face recognition systems.
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.

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Volume Title: Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)
Series: Advances in Intelligent Systems Research
Publication Date: 25 June 2025
ISBN: 978-94-6463-740-3
ISSN: 1951-6851
DOI: 10.2991/978-94-6463-740-3_18 How to use a DOI?
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

ris enw bib

TY  - CONF
AU  - Aaditya Prabal Chawla
AU  - S. Ebenezer Juliet
AU  - Ankur Suman
AU  - Aqif Khan
AU  - G. Manikandan
PY  - 2025
DA  - 2025/06/25
TI  - Deep Learning based Multi-face Recognition System for Automatic Attendance Registering in Classrooms
BT  - Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)
PB  - Atlantis Press
SP  - 203
EP  - 214
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-740-3_18
DO  - 10.2991/978-94-6463-740-3_18
ID  - Chawla2025
ER  -

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