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Research on Action Recognition and Content Analysis in Videos Based on DNN and MLN

Wei Song1,2,*, Jing Yu3, Xiaobing Zhao1,2, Antai Wang4
1 School of Information Engineering, Minzu University of China, Beijing, 100081, China.
2 National language resource monitoring & Research Center Minority Languages Branch, Minzu University of China, Beijing, 100081, China.
3 School of Electronic Information Engineering, Beijing Jiaotong University, Beijing, 100044, China.
4 New Jersey Institute of Technology, 323 Dr Martin Luther King Jr Blvd. Newark, NJ, 07102, USA.
* Corresponding Author: Wei Song. Email: songwei@muc.edu.cn.

Computers, Materials & Continua 2019, 61(3), 1189-1204. https://doi.org/10.32604/cmc.2019.06361

Abstract

In the current era of multimedia information, it is increasingly urgent to realize intelligent video action recognition and content analysis. In the past few years, video action recognition, as an important direction in computer vision, has attracted many researchers and made much progress. First, this paper reviews the latest video action recognition methods based on Deep Neural Network and Markov Logic Network. Second, we analyze the characteristics of each method and the performance from the experiment results. Then compare the emphases of these methods and discuss the application scenarios. Finally, we consider and prospect the development trend and direction of this field.

Keywords

Video action recognition, deep learning network, markov logic network.

Cite This Article

W. Song, J. Yu, X. Zhao and A. Wang, "Research on action recognition and content analysis in videos based on dnn and mln," Computers, Materials & Continua, vol. 61, no.3, pp. 1189–1204, 2019.

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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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