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.

中文翻译：

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用于在线面试和考试的作弊检测管道

由于流行病和远程工作环境的优势，远程考试和工作面试变得流行并变得不可或缺。大多数公司和学术机构将这些系统用于招聘流程和在线考试。然而，远程考试系统的关键问题之一是在可靠的环境中进行考试。在这项工作中，我们提出了一个用于在线面试和考试的作弊分析管道。系统只需要考生的视频，并在考试期间录制。然后使用作弊检测管道来检测另一个人、电子设备使用情况和候选人缺席状态。该管道由人脸检测、人脸识别、对象检测和人脸跟踪算法组成。为了评估管道的性能，我们收集了一个私有视频数据集。视频数据集包括作弊活动和干净视频。最终，我们的管道提供了有效且快速的指南，用于检测和分析在线面试和考试视频中的作弊活动。