Baseline Estimation in Face Detection for AI Proctored Examinations through Convoluted Neural Networks

Abdelrahman Shata, Zineddine N. Haitaamar, A. Benkrid
{"title":"Baseline Estimation in Face Detection for AI Proctored Examinations through Convoluted Neural Networks","authors":"Abdelrahman Shata, Zineddine N. Haitaamar, A. Benkrid","doi":"10.1109/ITIKD56332.2023.10100328","DOIUrl":null,"url":null,"abstract":"The COVID-19 pandemic took the world by surprise, and everything came to a halt. The education sector had to adjust accordingly by shifting to online learning. If the online delivery experience was overall successful, assessment integrity becomes questionable as examinees still manage to circumvent the anti-plagiarism mechanism put in place. In this paper, we propose an artificial intelligence solution using face and head pose detection to estimate the neutral position of the examinee which will form the basis to detect any suspicious behavior. The resulting implementation achieved a 97% accuracy when detecting the examinee in the frame and a 98% accuracy when there are multiple faces detected.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITIKD56332.2023.10100328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The COVID-19 pandemic took the world by surprise, and everything came to a halt. The education sector had to adjust accordingly by shifting to online learning. If the online delivery experience was overall successful, assessment integrity becomes questionable as examinees still manage to circumvent the anti-plagiarism mechanism put in place. In this paper, we propose an artificial intelligence solution using face and head pose detection to estimate the neutral position of the examinee which will form the basis to detect any suspicious behavior. The resulting implementation achieved a 97% accuracy when detecting the examinee in the frame and a 98% accuracy when there are multiple faces detected.
基于卷积神经网络的人工智能监考人脸检测基线估计
2019冠状病毒病大流行震惊世界,一切都停止了。教育部门不得不相应地调整,转向在线学习。如果在线交付体验总体上是成功的,评估的完整性就会受到质疑,因为考生仍然设法绕过已经到位的反剽窃机制。在本文中,我们提出了一种人工智能解决方案,使用面部和头部姿势检测来估计考生的中立位置,这将成为检测任何可疑行为的基础。当检测到帧中的考生时,最终实现的准确率为97%,当检测到多个人脸时,准确率为98%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信