|Table of Contents|

Human Action Recognition Based on 3D-CBAM Attention Mechanism(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2021年01期
Page:
49-56
Research Field:
计算机科学与技术
Publishing date:

Info

Title:
Human Action Recognition Based on 3D-CBAM Attention Mechanism
Author(s):
Wang Fei; Hu Ronglin; Jin Ying
School of Computer and Software Engineering,Huaiyin Institute of Technology,Huaian 223003,China
Keywords:
machine vision; human movement recognition; 3D convolutional neural network; attention mechanism
PACS:
TP391.4
DOI:
10.3969/j.issn.1672-1292.2021.01.008
Abstract:
Aiming at the problems of insufficient feature extraction and low recognition rate of existing action recognition methods,the paper proposes a fusion model by combining the advantages of two-stream network,3D convolutional neural network and convolutional LSTM network. In order to better extract human motion features,the fusion model adopts SSD target detection method to segment the human body as local features and global features of the original video for joint training,and adopts late fusion for classification. The 3D convolutional block attention module(3D-CBAM)is integrated into 3D convolutional neural network by using shortcut structure to enhance the neural network’s channel and spatial feature extraction. And by replacing part of the 3D convolutional layer of the neural network with ConvLSTM layer,the temporal relation of the video is better obtained. The experiment is carried out on the KTH dataset,and the results show that the proposed model has high recognition accuracy of human action.

References:

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Last Update: 2021-03-15