TY - JOUR
T1 - Research on action recognition and content analysis in videos based on DNN and MLN
AU - Song, Wei
AU - Yu, Jing
AU - Zhao, Xiaobing
AU - Wang, Antai
N1 - Funding Information:
Acknowledgement: This work was supported in part by National Science Foundation Project of P. R. China (Grant Nos. 61503424, 61331013), Promotion plan for young teachers’ scientific research ability of Minzu University of China, Youth Academic Team Leadership Project, MUC111 and the First-class University and First-class Discipline of Minzu University of China (“intelligent computing and network security”). Our gratitude is extended to the anonymous reviewers for their valuable comments and professional contributions to their improvement of this paper.
Publisher Copyright:
© 2019 Tech Science Press. All rights reserved.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Deep learning network
KW - Markov logic network
KW - Video action recognition
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U2 - 10.32604/cmc.2019.06361
DO - 10.32604/cmc.2019.06361
M3 - Article
AN - SCOPUS:85075264756
SN - 1546-2218
VL - 61
SP - 1189
EP - 1204
JO - Computers, Materials and Continua
JF - Computers, Materials and Continua
IS - 3
ER -