Implementing CCTV-Based Attendance Taking Support System Using Deep Face Recognition: A Case Study at FPT Polytechnic College

Symmetry

BuiDinh Chien¹  TranQuy Ban¹  DuongXuan Hoa¹  LePhuong Chi¹  NgoTung Son¹  BuiNgoc Anh¹  LeVan Thanh¹  TranQuang Huy¹  LeDinh Duy¹  Muhammad Hassan Raza Khan² 

[1] Information and Communication Technology Department, FPT University, Hanoi 100000, Vietnam;Mathematical Department, University of Padova, 35100 Padova, Italy;

关键词: face recognition;    cctv;    attendance taking system;    deep learning;    computer vision;   

DOI  :  10.3390/sym12020307

来源: DOAJ

【 摘 要 】

Face recognition (FR) has received considerable attention in the field of security, especially in the use of closed-circuit television (CCTV) cameras in security monitoring. Although significant advances in the field of computer vision are made, advanced face recognition systems provide satisfactory performance only in controlled conditions. They deteriorate significantly in the face of real-world scenarios such as lighting conditions, motion blur, camera resolution, etc. This article shows how we design, implement, and conduct the empirical comparisons of machine learning open libraries in building attendance taking (AT) support systems using indoor security cameras called ATSS. Our trial system was deployed to record the appearances of 120 students in five classes who study on the third floor of FPT Polytechnic College building. Our design allows for flexible system scaling, and it is not only usable for a school but a generic attendance system with CCTV. The measurement results show that the accuracy is suitable for many different environments.

【 授权许可】

Unknown