Remote examination and job interviews have gained popularity and become indispensable because of both pandemics and the advantage of remote working circumstances. Most companies and academic institutions utilize these systems for their recruitment processes and also for online exams. However, one of the critical problems of the remote examination systems is conducting the exams in a reliable environment. In this work, we present a cheating analysis pipeline for online interviews and exams. The system only requires a video of the candidate, which is recorded during the exam. Then cheating detection pipeline is employed to detect another person, electronic device usage, and candidate absence status. The pipeline consists of face detection, face recognition, object detection, and face tracking algorithms. To evaluate the performance of the pipeline we collected a private video dataset. The video dataset includes both cheating activities and clean videos. Ultimately, our pipeline presents an efficient and fast guideline to detect and analyze cheating activities in an online interview and exam video.
翻译：远程考试和工作面试由于流行病和远程工作环境的优势而越来越受欢迎,变得不可或缺。大多数公司和学术机构利用这些系统进行招聘过程和在线考试。然而,远程考试系统的一个关键问题是在可靠的环境中进行考试。在这项工作中,我们为在线面试和考试提供了欺骗性分析管道。该系统只要求候选人的视频,并在考试中记录。然后,欺骗性检测管道被用来检测另一个人、电子设备使用和候选人缺勤状态。管道包括面部检测、面部识别、物体检测和面对面跟踪算法。为了评估输油管的运行情况,我们收集了一个私人视频数据集。视频数据集包括欺骗活动和清洁视频。最终,我们的输油管道为在在线访谈和考试视频中检测和分析欺骗活动提供了高效和快速的指导方针。
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