Multi-view Human Action Recognition Based on Deep Neural Network

Authors

Zhao Ying, 1. Beijing Laboratory of Intelligent Information Technology, Beijing Institute of Technology, Beijing 100081, China; ;2. Teachers College, Beijing Union University, Beijing 100011, China; ;
Lu Yao, 1. Beijing Laboratory of Intelligent Information Technology, Beijing Institute of Technology, Beijing 100081, China; ;
Zhang Jian, 3. School of Computer Science and Engineering, Central South University, Changsha 410083, China;
Qidi Liang, 3. School of Computer Science and Engineering, Central South University, Changsha 410083, China;
Long Wei, 1. Beijing Laboratory of Intelligent Information Technology, Beijing Institute of Technology, Beijing 100081, China; ;

Abstract

Abstract: A novel deep neural network named CNN+CA(Convolutional Neural Network plus Context Attention) model is constructed and a new recognition algorithm based on sequence matching is presented to improve the recognition accuracy of MVHAR (Multi-view Human Action Recognition). A CNN(Convolutional Neural Network) is designed to automatically learn multi-view fusion features; the CA (Context Attention) module is introduced to selectively focus on the parts of the features that are relevant for the recognition task; the proposed recognition algorithm based on sequence matching is used to realize MVHAR. The experimental results on the IXMAS dataset and the i3DPost dataset demonstrate that the recognition accuracy of the proposed method is higher than those of the state-of-the-art MVHAR methods.

Recommended Citation

Ying, Zhao; Yao, Lu; Jian, Zhang; Liang, Qidi; and Wei, Long (2021) "Multi-view Human Action Recognition Based on Deep Neural Network," Journal of System Simulation: Vol. 33: Iss. 5, Article 3.
DOI: 10.16182/j.issn1004731x.joss.19-0448
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss5/3

First Page

1019

Revised Date

2019-10-08

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-0448

Last Page

1030

CLC

TP391

Recommended Citation

Zhao Ying, Lu Yao, Zhang Jian, Liang Qidi, Long Wei. Multi-view Human Action Recognition Based on Deep Neural Network[J]. Journal of System Simulation, 2021, 33(5): 1019-1030.

DOI

10.16182/j.issn1004731x.joss.19-0448