Automatic abnormal detection of video homework is an effective method to improve the efficiency of homework marking. Based on the video homework review of “big data acquisition and processing project of actual combat” and other courses, this paper found some student upload their videos with poor images, face loss or abnormal video direction. However, it is time-consuming for teachers to pick out the abnormal video homework manually, which results in prompt feedback to students. This paper puts forward the AVHADS (Abnormal Video Homework Automatic Detection System). The system uses suffix and parameter identification, Open CV, and the audio classification model based on MFCC feature to realize the automatic detection and feedback of abnormal video homework. Experimental results show the AVHADS is feasible and effective.

视频作业异常自动检测是提高作业批改效率的有效方法。通过“实战大数据采集与处理项目”等课程的视频作业复习，发现部分学生上传的视频画质不佳、人脸丢失或视频方向异常。然而，教师手动挑选异常的视频作业非常耗时，导致及时反馈给学生。本文提出了AVHADS（异常视频作业自动检测系统）。系统采用后缀参数识别、Open CV、基于MFCC特征的音频分类模型，实现视频作业异常的自动检测与反馈。实验结果表明，AVHADS是可行和有效的。