计算机工程与应用 ›› 2021, Vol. 57 ›› Issue (6): 225-231.DOI: 10.3778/j.issn.1002-8331.1912-0187

• 工程与应用 • 上一篇    下一篇

基于深度学习的关键岗位人员行为分析系统

云旭,宋焕生,梁浩翔,侯景严,戴喆   

  1. 长安大学 信息工程学院,西安 710064
  • 出版日期:2021-03-15 发布日期:2021-03-12

Personnel Behavior Analysis System for Key Positions Based on Deep Learning

YUN Xu, SONG Huansheng, LIANG Haoxiang, HOU Jingyan, DAI Zhe   

  1. School of Information Engineering, Chang’an University, Xi’an 710064, China
  • Online:2021-03-15 Published:2021-03-12

摘要:

针对关键岗位的人员行为分析的问题,提出了一种基于视频的行为分析方法。制作了包含多姿态样本的岗位人员行为数据集,并使用YOLOv3网络训练该数据集得到行为检测模型。使用提出的人员行为分析算法结合行为检测模型对视频进行处理,对人员行为进行初步分析。在人员行为分析算法的基础上,结合图像相似度和明暗度等特征,进行深度分析并给出离岗、睡觉和玩手机事件的判断结果。实验结果表明,制作的数据集在人员行为检测中有较高的检测精度,同时行为分析的准确度也较高,并且能够进行实时处理。

关键词: 目标检测, 行为分析, 深度学习, 目标数据集, 图像处理

Abstract:

Aiming at the problem of human behavior analysisin key positions, a video-based behavior analysis method is proposed. A personnel behavior dataset containing multiple pose samples is produced, which is trained by the YOLOv3 network to obtain a behavior detection model. The proposed human behavior analysis algorithm combined with the model is used to process video and conduct a preliminary analysis of human behavior. Based on the human behavior analysis algorithm, combined with image similarity, brightness and darkness and other characteristics, in-depth analysis is carried out and the judgment results of leaving, sleeping and playing mobile phone are given. The experimental results show that the produced dataset has higher detection accuracy in human behavior detection, and the accuracy of behavior analysis is extremely high, and it can be processed in real time.

Key words: object detection, behavior analysis, deep learning, object dataset, image process