基于全局分割图卷积网络的骨骼双人交互行为识别OA
Skeleton-based Double Human Interaction Recognition Based on Global Segmentation Graph Convolutional Network
图卷积网络(GCN)在双人交互识别方面应用非常广泛,但是传统图卷积网络对于节点特征的学习不够充分,尤其在双人交互行为中,每个节点的特征往往包含多个人的信息,导致节点特征不够准确.为了有效提取双人交互行为关节点之间的相关性特征,聚合双人之间的特征信息,提出全局分割图卷积网络(GS-GCN),进行基于骨骼的双人交互行为识别.GS-GCN包含全局分割图卷积(GSGC)和层次聚合注意力(HAA)模块,GSGC将图卷积(GCN)和全局分割图(GS-Grap…查看全部>>
Graph convolutional network(GCN)is widely used in interaction recognition,but the traditional graph convolutional network is not enough to learn node features.Especially in interaction,the features of each node often contain information of multiple people,resulting in inaccurate node features.In order to effectively extract the correlation features between the nodes between interaction behaviors and aggregate the feature information,a global segmentation gra…查看全部>>
徐寅虎
南京邮电大学 计算机学院、软件学院、网络空间安全学院,江苏 南京 210023
计算机与自动化
双人交互识别图卷积网络邻接矩阵注意力模块
human interaction recognitiongraph convolution networkadjacency matrixattention module
《软件导刊》 2024 (6)
157-162,6
评论