Abstract
Abstract: As the world is shifting towards digitalization, mostof the exams and assessments are being conducted online. These exams must be proctored. Several students are accessing thetest at the same time. It is very difficult to manually look if a student is committing malpractice. This project aims to use face detection and recognition for proctoring exams. Face detectionis the process of detecting faces in a video or image while face recognition is identifying or verifying a face from images orvideos. There are several research studies done on the detectionand recognition of faces owing to the requirement for securityfor economic transactions, authorization, national safety andsecurity, and other important factors. Exam proctoring platformsshould be capable of detecting cheating and malpractices like face is not on the screen, gaze estimation, mobile phone detection,multiple face detection, etc. This project uses face identificationusing HAAR Cascades Algorithm and face recognition using theLocal Binary Pattern Histogram algorithm. This system can beused in the future in corporate offices, schools, and universities.
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