计算机工程与应用2024，Vol.60Issue(8)：250-257,8.DOI:10.3778/j.issn.1002-8331.2212-0110
基于时空特征融合的交通警察手势识别
Gesture Recognition of Traffic Police Based on Spatio-Temporal Feature Fusion
摘要
Abstract
In recent years,with the development of human pose estimation technology,gesture recognition technology based on skeleton key points comes into being.This paper proposes a GCPM-AGRU model for gesture recognition of traffic police.In order to locate the key points of human body more accurately,the convolution pose machine(CPM)is improved.Firstly,the idea of residuals,channel split and channel shuffle are added to the feature extraction module,so that the designed feature extraction module can better extract image features.In addition,the parallel multi-branch Incep-tion4d structure is added in the first stage of CPM,which makes the CPM network have the idea of multi-scale feature fusion,and effectively improves the problem of human key point location.Secondly,a GRU based on attention mecha-nism is proposed,which allocates different weights to each frame to achieve different degrees of attention to each frame,so as to obtain better time information.Finally,it combines the spatio-temporal feature information to carry out traffic police gesture recognition.The accuracy of traffic police gesture recognition reaches 93.7%,which is 2.95 percentage points higher than before the improvement of network.关键词
手势识别/人体关键点/卷积姿态机/GRU/时空特征信息Key words
gesture recognition/human body key points/convolution attitude machine/GRU/spatio-temporal feature information分类
信息技术与安全科学引用本文复制引用
杜兵,赵骥..基于时空特征融合的交通警察手势识别[J].计算机工程与应用,2024,60(8):250-257,8.基金项目
辽宁自然科学基金(2020-MS-281) （2020-MS-281）
辽宁省教育厅科研项目(LJKZZ2022043). （LJKZZ2022043）
