This document summarizes an automated online exam proctoring system that uses audio and video from a webcam and microphone to continuously monitor test takers and detect potential cheating behaviors during online exams. The system analyzes visual and audio cues like user verification, text detection, voice detection, active window detection, gaze estimation and phone detection to classify if the test taker is cheating. An evaluation with 24 subjects performing various cheating behaviors while taking online exams showed the system can accurately and robustly detect cheating in real-time. The system aims to maintain academic integrity for online exams by providing automated proctoring to replace costly human proctoring.

Automated Online Exam Proctoring: Yousef Atoum, Liping Chen, Alex X. Liu, Stephen D. H. Hsu, and Xiaoming Liu PDF

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