计算机应用与软件2024，Vol.41Issue(8)：319-325,7.DOI:10.3969/j.issn.1000-386x.2024.08.046
基于scSE非局部双流ResNet网络的行为识别
ACTION RECOGNITION ALGORITHM FOR NON-LOCAL TWO-STREAM RESNET NETWORK BASED ON SCSE FUSION
摘要
Abstract
Aimed at the problem of low recognition rate of video frames containing redundant information in dual-stream network,scSE(Spatial and Channel Squeeze & Excitation Block)and non-local operation are introduced based on two-stream network to construct SC_NLResNet behavior recognition framework.In this framework,the framework divided the video into equal and non-overlapping temporal segments and sparsely sampled each segment,extracting RGB frames and optical flow graphs as the input of the scSE module.The features processed by scSE were inputted into the non-local two-stream ResNet network,and the segmentations were merged to obtain the final prediction results.The experimental accuracy on UCF101 and Hmdb51 dataset reaches 96.9％and 76.2％,respectively.The results show that the combination of non-local operation and scSE module can enhance the information of feature space-time and between the channels to improve the accuracy,which verifies the effectiveness of SC_NLResNet network.关键词
双流卷积神经网络/scSE模块/残差网络/非局部操作/行为识别Key words
Two-stream convolutional neural network/ScSE module/Residual neural network/Non-local operation/Action recognition分类
信息技术与安全科学引用本文复制引用
李占利,王佳莹,靳红梅,李洪安..基于scSE非局部双流ResNet网络的行为识别[J].计算机应用与软件,2024,41(8):319-325,7.基金项目
陕西省自然科学基础研究计划项目(2019JM-348,2019JLM-10). （2019JM-348,2019JLM-10）
