福建电脑2025，Vol.41Issue(1)：1-10,10.DOI:10.16707/j.cnki.fjpc.2025.01.001
三流时空步态神经网络用于Kinect身份鉴定
Three Stream Spatiotemporal Gait Neural Network for Kinect Identity Authentication
严云飞1
作者信息
- 1. 福建师范大学计算机与网络空间安全学院 福州 350117
- 折叠
摘要
Abstract
Gait recognition is a biometric recognition technology.To improve the accuracy of gait recognition in corridor scenes,this paper proposes a hybrid deep learning model using three stream graph structured data.The model is based on both temporal and spatial convolutional networks to fully extract the most representative spatiotemporal gait dynamic features from gait maps.Through experiments on normal gait data of 30 subjects,the results showed that the maximum accuracy of this method reached 99.58%,indicating that the method can learn spatiotemporal differences in gait features.关键词
时空步态分析/身份鉴定/图神经网络/特征提取Key words
Spatiotemporal Gait Analysis/Person Identification/GCN/Feature Extraction分类
信息技术与安全科学引用本文复制引用
严云飞..三流时空步态神经网络用于Kinect身份鉴定[J].福建电脑,2025,41(1):1-10,10.
