S. Poornima, N. Sripriya, B. Vijayalakshmi, P. Vishnupriya
{"title":"Attendance monitoring system using facial recognition with audio output and gender classification","authors":"S. Poornima, N. Sripriya, B. Vijayalakshmi, P. Vishnupriya","doi":"10.1109/ICCCSP.2017.7944103","DOIUrl":null,"url":null,"abstract":"Maintaining and taking log of attendance in a class is not much effective through manual process. Since bunking the classes or giving proxies for the absentees become fun and fantasy among the current generation students. Manual entering of attendance in logbooks becomes a difficult task and it can be easily manipulated. Therefore, this paper aims in presenting an automated attendance System — AUDACE. This system automatically detects the student in the class room and marks the attendance by recognizing their face. This system is developed by capturing real time human faces in the class. The detected faces are matched against the reference faces in the dataset and marked the attendance for the attendees. Finally the absentee lists are said aloud through voice conversion system for confirmation. Secondly, the system is trained to classify the gender of the students present in the class.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCSP.2017.7944103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Maintaining and taking log of attendance in a class is not much effective through manual process. Since bunking the classes or giving proxies for the absentees become fun and fantasy among the current generation students. Manual entering of attendance in logbooks becomes a difficult task and it can be easily manipulated. Therefore, this paper aims in presenting an automated attendance System — AUDACE. This system automatically detects the student in the class room and marks the attendance by recognizing their face. This system is developed by capturing real time human faces in the class. The detected faces are matched against the reference faces in the dataset and marked the attendance for the attendees. Finally the absentee lists are said aloud through voice conversion system for confirmation. Secondly, the system is trained to classify the gender of the students present in the class.