舰船电子工程2025，Vol.45Issue(3)：38-42,5.DOI:10.3969/j.issn.1672-9730.2025.03.009
基于深度学习的人体持有武器识别研究
Research on Weapon Recognition of Human Body Based on Deep Learning
黄兆年 1卢龙生 2程朋 1李恒1
作者信息
- 1. 武汉数字工程研究所 武汉 430205
- 2. 广州市长岛光电机械厂 广州 510336
- 折叠
摘要
Abstract
This paper proposes a method based on the improved ST-GCN and YOLOv5 to identify whether a person is carrying a weapon.In this method,a single frame is extracted from the border surveillance video as a unit to extract the skeleton point infor-mation of the human body,and then multi-frame image information is aggregated by using the ST-GCN as a framework to identify the movement of the person.Then,the relationship between personnel and weapons can be detected by YOLOv5 and human skele-ton to determine whether personnel in motion carry weapons.Finally,experiments are conducted to verify the effectiveness of the method.The results show that the method can make full use of the spatio-temporal information between the skeleton points in multi-frame images to accurately identify the movement of people and whether they carry weapons,with good accuracy and robust-ness.关键词
动作识别/武器识别/骨架信息提取/时空图卷积神经网络Key words
action recognition/weapon recognition/skeleton information extraction/ST-GCN分类
信息技术与安全科学引用本文复制引用
黄兆年,卢龙生,程朋,李恒..基于深度学习的人体持有武器识别研究[J].舰船电子工程,2025,45(3):38-42,5.
