Abnormal video homework automatic detection system

Abstract

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.