计算机与数字工程2023，Vol.51Issue(12)：2841-2845,2851,6.DOI:10.3969/j.issn.1672-9722.2023.12.014
基于残差时移模块和双流网络的手语识别方法
Method of Sign Language Recognition Based on Temporal Shift Module and Two-Stream Networks
摘要
Abstract
In the existing sign language recognition methods,multimodal images are widely used,but the multimodal data is complex and difficult to operate.In addition,the existing sign language recognition methods can not effectively aggregate the global information of human body and the local information of motion region.In order to improve the sign language recognition method,this paper proposes a sign language recognition method based on residual temporal shift module and two-stream networks,which only us-es RGB image.The two branches of two-stream networks are improved to global image branch and local branch of motion region.The semantic segmentation algorithm is used to solve the problem of hand localization.The two branches effectively aggregate the global information and the motion region information through data fusion.Experiments on SLR500 open source dataset show that the recognition rate of this method is up to 94.7%.关键词
手语识别/双流网络/时域位移/全局特征/运动区域局部分割/数据融合Key words
sign language recognition/two-stream networks/temporal shift/global feature/local semantic segmentation of moving region/data fusion分类
信息技术与安全科学引用本文复制引用
蔡畅,林靖宇..基于残差时移模块和双流网络的手语识别方法[J].计算机与数字工程,2023,51(12):2841-2845,2851,6.基金项目
国家自然科学基金项目(编号:61561005) （编号:61561005）
广西研究生教育创新计划(编号:YCSW2019026)资助. （编号:YCSW2019026）
