Paper
28 February 2024 Research on intelligent attendance management system based on face recognition technology
Xiaoxue Zong, Kang Feng
Author Affiliations +
Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 130713K (2024) https://doi.org/10.1117/12.3025538
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China
Abstract
As a biometric recognition technology, face recognition has the characteristics of universality, high reliability and strong individual differences, and has broad application prospects in the field of smart security. According to the needs of the access control and attendance system in the construction of the school's smart campus, this paper applies the face recognition algorithm based on deep learning to the face recognition access control and attendance system, and makes lightweight improvements to the algorithm to address the common problem of large amounts of calculation. This paper uses the improved RetainNet face detection model to design and implement an automatic attendance system based on face recognition for the classroom scene. Based on the classroom surveillance video stream, face detection is first performed, and the face filtering method is used after obtaining the face image set. Eliminate face images with low face quality and successfully recognized positions, then perform face super-resolution and face alignment, and finally send them to the face recognition model for face comparison to complete attendance. Experiments show that the improvements proposed in this article effectively improve the accuracy of classroom face detection.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xiaoxue Zong and Kang Feng "Research on intelligent attendance management system based on face recognition technology", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 130713K (28 February 2024); https://doi.org/10.1117/12.3025538
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KEYWORDS
Facial recognition systems

Detection and tracking algorithms

Education and training

Deep learning

Intelligence systems

Object detection

Data modeling

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