• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science ›› 2021, Vol. 43 ›› Issue (12): 2206-2215.

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Overview of human behavior detection methods based on deep learning

LU Wei-zhong1,2,SONG Zheng-wei1,WU Hong-jie1,2,CAO Yan1,DING Yi-jie1,2,ZHANG Yu3   

  1. (1.School of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou 215009;

    2.Jiangsu Provincial Key Laboratory of Building Intelligence and Energy Saving,Suzhou 215009;

    3.Suzhou Industrial Park Industrial Technology School,Suzhou 215123,China)
  • Received:2020-04-30 Revised:2020-09-08 Accepted:2021-12-25 Online:2021-12-25 Published:2021-12-31

Abstract: Behavior detection is a research hotspot in the field of video understanding and computer vision, which attracts the attention of scholars at home and abroad. It has been widely used in many fields such as intelligent surveillance and human-computer interaction. With the development of techno- logy, deep learning has made a great breakthrough in image classification. The application of the recognition methods based on deep learning to human behavior detection has become a hotspot. Therefore, the paper firstly introduces several datasets commonly used in behavior detection, and the research status of deep learning in the field of behavior detection in recent years. Then, the basic process of behavior detection methods and recognition methods based on deep learning are analyzed. Finally, the future development trend and possible shortcomings are analyzed from the aspects of method performance and application prospect.


Key words: deep learning, human behavior detection, intelligent surveillance, behavior dataset