基于人脸识别的实时大学课堂考勤系统

Hajrah Sultan, Muhammad Hamza Zafar, Saba Anwer, Asim Waris, Haris Ijaz, Moaz Sarwar
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引用次数: 2

摘要

在过去的几年里,人工智能领域取得了重大进展。本文提出了一种基于人脸识别的考勤系统。该系统不仅可以记录考勤,还可以制作excel表格,以保证考勤记录的安全性。该系统也成功地识别了来自不同方向的人脸。首先用高清1080p摄像机采集人脸图像,然后进行降噪处理,利用直方图定向梯度(HOG)技术检测人脸的筋膜特征。本系统采用了Dlib人脸识别API,人脸识别准确率为97.38%。系统可以识别出画面中出现的所有学生,并对所有与数据库特征匹配的学生进行记录。该系统还能够从多个方向识别学生的面部。本系统也可以实现基于人脸识别的概念,制定一个在特定机构设置的全证明监控。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real Time Face Recognition Based Attendance System For University Classroom
Over past few years there have been significant improvements in the field of artificial intelligence. In presented paper an automatic attendance marking setup based on the concept of face recognition has been proposed. Presented system not only mark the attendance but make an excel sheet to keep the record safe. This system successfully identifies the faces from different directions as well. First an HD 1080p camera captures the face images and then after noise reduction, histogram-oriented gradient (HOG) technique is used to detect the fascial features. Dlib face recognition API has been used in this system with 97.38 % accuracy of face recognition. System can recognize all the students present in the frame and make the record of all those students whose features matches with the database. Presented system is also capable of recognizing the students' face from multiple directions. This system can also be implemented to formulate a full proof surveillance set up in certain organization based on the concept of face recognition.
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