Automated online exam proctoring system using computer vision and hybrid ML classifier

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bracu.type.groupResearch Publications
datacite.rightsMetadata Only
dc.contributor.authorHossain, Zarin Tahia
dc.contributor.authorRoy, Protyasha
dc.contributor.authorNasir, Rina
dc.contributor.authorNawsheen, Sumaiya
dc.contributor.authorHossain, Muhammad Iqbal
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2026-08-15T13:39:26Z
dc.date.available2026-08-15T13:39:26Z
dc.date.issued2021-01-01
dc.description.abstractImportance of online education can be seen especially during the ongoing Covid-19 when going to schools or colleges is not possible. So validity of online exams should also be maintained with respect to traditional pen-paper examinations. However, absence of invigilator makes it easy for the examinees to cheat during the exam. Though there are already many systems for online proctoring, not all educational institutes can afford them as the systems are very expensive. In this paper, we have used eye gaze and head pose estimation as the main features to design our online proctoring system. Therefore, the purpose of this paper is to use these features to create an online proctoring system using computer vision and machine learning and stop cheating attempts in exams.
dc.description.versionPublished
dc.format.extent14-17
dc.identifier.citationZ. T. Hossain, P. Roy, R. Nasir, S. Nawsheen and M. I. Hossain, "Automated Online Exam Proctoring System Using Computer Vision and Hybrid ML Classifier," 2021 IEEE International Conference on Robotics, Automation, Artificial-Intelligence and Internet-of-Things (RAAICON), Dhaka, Bangladesh, 2021, pp. 14-17, doi: 10.1109/RAAICON54709.2021.9929456.
dc.identifier.doi10.1109/RAAICON54709.2021.9929456
dc.identifier.issn9781665478694
dc.identifier.other2-s2.0-85142758281
dc.identifier.urihttps://hdl.handle.net/10361/29093
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.hasversion10.1109/RAAICON54709.2021.9929456
dc.relation.ispartofProceedings of 2021 IEEE International Conference on Robotics Automation Artificial Intelligence and Internet of Things Raaicon 2021
dc.relation.ispartofseriesProceedings of 2021 IEEE International Conference on Robotics Automation Artificial Intelligence and Internet of Things Raaicon 2021
dc.relation.urihttps://ieeexplore.ieee.org/document/9929456
dc.rightsfalse
dc.subjectCheating prediction
dc.subjectHybrid classifier
dc.subjectMachine learning
dc.subjectMLP
dc.subjectOnline proctoring
dc.subjectXGBoost
dc.subject.lcshComputer vision.
dc.subject.lcshMachine learning.
dc.titleAutomated online exam proctoring system using computer vision and hybrid ML classifier
dc.typeConference Proceeding
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.identifier.scopus-author-id57983759300
person.identifier.scopus-author-id57982355300
person.identifier.scopus-author-id57983997500
person.identifier.scopus-author-id57983529000
person.identifier.scopus-author-id57799191800

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