计算机应用与软件2024，Vol.41Issue(12)：193-200,274,9.DOI:10.3969/j.issn.1000-386x.2024.12.028
基于骨架序列的校园斗殴行为检测研究
CAMPUS FIGHTING BEHAVIOR DETECTION BASED ON SKELETON SEQUENCES
姚砺 1王梦珂 1万燕1
作者信息
- 1. 东华大学计算机科学与技术学院 上海 201600
- 折叠
摘要
Abstract
In the field of campus security,the identification of violent behaviors currently mainly relies on manual labor,which is prone to omissions.Skeleton-based spatio-temporal graph convolutional network(ST-GCN)has high behavior recognition accuracy,but it is mainly used for single person recognition.This paper proposes a method of identifying violence against campus surveillance video,which adds a multi-target tracking module on the basis of ST-GCN.The OpenPose algorithm was used to obtain the human skeleton set in the video frame,and the single-person skeleton sequence was separated by the Markov chain Monte Carlo data association method and input into ST-GCN for violent behavior recognition.The experimental results on the data set RWF-2000 show that the recognition rate of this method reaches 87.75%,which is higher than other existing models.关键词
多目标跟踪/暴力检测/行为识别Key words
Multi-target tracking/Violence detection/Behavior recognition分类
信息技术与安全科学引用本文复制引用
姚砺,王梦珂,万燕..基于骨架序列的校园斗殴行为检测研究[J].计算机应用与软件,2024,41(12):193-200,274,9.
