Overview of behavior recognition based on deep learning

被引：0
作者：
Kai Hu
Junlan Jin
Fei Zheng
Liguo Weng
Yiwu Ding
机构：
[1] Nanjing University of Information Science and Technology,School of Automation
[2] Nanjing University of Information Science and Technology,Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET)
[3] China Telecom Ningbo Branch,Innovation Department of Industrial Internet
来源：
Artificial Intelligence Review | 2023年 / 56卷
关键词：
Behavior recognition; Deep learning; Skeleton data;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Human behavior recognition has always been a hot spot for research in computer vision. With the wide application of behavior recognition in virtual reality and short video in recent years and the rapid development of deep learning algorithms, behavior recognition algorithms based on deep learning have emerged. Compared with traditional methods, behavior recognition algorithms based on deep learning have the advantages of strong robustness and high accuracy. This paper systemizes and introduces behavior recognition algorithms based on deep learning proposed in recent years, then focuses on a series of behavior recognition algorithms based on image and bone data; deeply analyzes their theories and performance, and finally, puts forward further prospects.
引用
收藏
页码：1833 / 1865
页数：32
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