基于scSE非局部双流ResNet网络的行为识别OA北大核心CSTPCD

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.