{"title":"Human Face Detection and Recognition from the Video Using Deep Learning","authors":"Hemlata Sinha, Sumit Roy","doi":"10.52783/cienceng.v11i1.103","DOIUrl":null,"url":null,"abstract":" Attendance management can be a significant burden on teachers if done manually. To solve this problem, It is proposed that we use an intelligent and automatic presence management system. Using this framework, the problem of proxies and tagged students present while they are not physically present can easily be resolved. This system marks the attendance using live video stream. The frames are extracted from video using Open CV. The main implementation stages used in this type of system are detection and recognition of the detected face, for which dlib is used. After this, the connection of the acknowledged faces should be conceivable by comparing with the database containing the faces of the students. It will be an effective technique to manage student attendance..","PeriodicalId":214525,"journal":{"name":"Proceeding International Conference on Science and Engineering","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceeding International Conference on Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52783/cienceng.v11i1.103","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
Attendance management can be a significant burden on teachers if done manually. To solve this problem, It is proposed that we use an intelligent and automatic presence management system. Using this framework, the problem of proxies and tagged students present while they are not physically present can easily be resolved. This system marks the attendance using live video stream. The frames are extracted from video using Open CV. The main implementation stages used in this type of system are detection and recognition of the detected face, for which dlib is used. After this, the connection of the acknowledged faces should be conceivable by comparing with the database containing the faces of the students. It will be an effective technique to manage student attendance..