南阳师范学院学报2024，Vol.23Issue(3)：52-59,8.
基于深度学习的实时监控图像中考生异常行为自动识别算法
An automatic recognition algorithm for abnormal behavior of candidates in real-time monitoring images based on deep learning
摘要
Abstract
With the construction of digital campus,real-time image acquisition equipment is generally installed in classroom.Therefor,there are good conditions to build smart examination rooms.Based on image processing technology,this paper proposes an algorithm to automatically and accurately identify abnormal behaviors in the examination,aiming to maintain the fairness of the examination,improving the efficiency of invigilation and standardizing the exam disciplines further.First,Mosaic technology is used to enhance the video frame image,thereby expanding the image set containing small targets.Secondly,the improved YOLOv5s object detection al-gorithm is used to locate the human detection box of the candidate's exam behavior status,quickly and accurately identifying the candidate's human position.Thirdly,SimplePose is used to locate the key points of the candi-date's body,further accurately describing the posture of the human body and more accurately identifying abnor-mal behavior.In addition,SimplePose is lightweight and can process the images and extract the key point infor-mation quickly to ensure real-time performance.Finally,ConvNeXt image classifier is utilized to classify the hu-man body key point images,which enhances the robustness and stability of the model.The experimental results show that the proposed real-time detection method has a fast detection performance for the identification of cheat-ing behavior of candidates in the examination environment,and the identification accuracy rate reaches 92.1%.It improves the efficiency of examination center supervision and maintains the fairness of the examination.关键词
图像处理技术/考生异常行为识别/YOLOv5s/SimplePose/ConvNeXt图像分类器Key words
image processing technology/identification of abnormal behavior among candidates/YOLOv5s/SimplePose/ConvNeXt image classifier分类
信息技术与安全科学引用本文复制引用
李书娴,柏长泽,张煜杰,赵雪峰..基于深度学习的实时监控图像中考生异常行为自动识别算法[J].南阳师范学院学报,2024,23(3):52-59,8.基金项目
国家自然科学基金项目(72174079) （72174079）
