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
{"title":"基于人脸识别的实时大学课堂考勤系统","authors":"Hajrah Sultan, Muhammad Hamza Zafar, Saba Anwer, Asim Waris, Haris Ijaz, Moaz Sarwar","doi":"10.1109/ICAI55435.2022.9773650","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":146842,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence (ICAI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Real Time Face Recognition Based Attendance System For University Classroom\",\"authors\":\"Hajrah Sultan, Muhammad Hamza Zafar, Saba Anwer, Asim Waris, Haris Ijaz, Moaz Sarwar\",\"doi\":\"10.1109/ICAI55435.2022.9773650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":146842,\"journal\":{\"name\":\"2022 2nd International Conference on Artificial Intelligence (ICAI)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Artificial Intelligence (ICAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAI55435.2022.9773650\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Artificial Intelligence (ICAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAI55435.2022.9773650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
LSTM-based Model for Forecasting of COVID-19 Vaccines in Pakistan Adaptive Neural-Sliding Mode Control of a Quadrotor Vehicle with Uncertainties and Disturbances Compensation A Force Myography based HMI for Classification of Upper Extremity Gestures Evolving computationally efficient prediction model for Stock Volatility using CGPANN A Review on Different Approaches for Assessing Student Attentiveness in Classroom using Behavioural Elements
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1