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交互关系超图卷积模型的双人交互行为识别

代金利 曹江涛 姬晓飞

智能系统学报2024,Vol.19Issue(2):316-324,9.
智能系统学报2024,Vol.19Issue(2):316-324,9.DOI:10.11992/tis.202208001

交互关系超图卷积模型的双人交互行为识别

Two-person interaction recognition based on the interactive relationship hypergraph convolution network model

代金利 1曹江涛 1姬晓飞2

作者信息

  • 1. 辽宁石油化工大学 信息与控制学院, 辽宁 抚顺 113001
  • 2. 沈阳航空航天大学 自动化学院, 辽宁 沈阳 110136
  • 折叠

摘要

Abstract

To enhance the security of schools,shopping malls,and other public places,it is important to achieve auto-matic identification of abnormal two-person interaction behaviors,such as stealing,robbing,fighting,and assaulting,in surveillance videos.However,the current behavior recognition method based on joint data in graph creation neglects the two-person interaction information as well as the interaction relationship between the single unnatural connection joints.To address this issue,a two-person interaction behavior recognition model based on the interactive relationship hyper-graph convolution network is proposed to model and identify human interactions.First,the corresponding single hyper-graph and two-person interaction graph are created for the joint-point data of each frame,where the hypergraph makes the information of multiple unnaturally connected nodes interchangeable at the same time,and the interaction graph em-phasizes the interaction strength between nodes.The above-constructed graph models are fed into the spatiotemporal graph convolution to model the spatial and temporal information separately,and lastly,the recognition results are ac-quired by the SoftMax classifier.The benefits of the proposed algorithm framework are that the interactive relationship between two persons,the structural relationship between unnatural connections,and the flexible motion characteristics of limbs are regarded in the graph construction process.Tests on the NTU data set demonstrate that the algorithm at-tains a correct recognition rate of 97.36%.The findings indicate that the network model enhances the ability to represent the characteristics of two-person interaction and has better recognition performance than the current models.

关键词

双人交互/行为识别/关节点数据/深度学习/时空图卷积网络/超图/图结构/神经网络

Key words

two-person interaction/behavior recognition/skeleton node data/deep learning/ST-GCN/hypergraph/graph structure/neural networks

分类

计算机与自动化

引用本文复制引用

代金利,曹江涛,姬晓飞..交互关系超图卷积模型的双人交互行为识别[J].智能系统学报,2024,19(2):316-324,9.

基金项目

国家自然科学基金项目(61673199) (61673199)

辽宁省科技公益研究基金项目(2016002006). (2016002006)

智能系统学报

OA北大核心CSTPCD

1673-4785

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