A Survey of Human Action Recognition and Posture Prediction

Nan Ma*, Zhixuan Wu, Yiu Ming Cheung, Yuchen Guo, Yue Gao, Jiahong Li, Beijyan Jiang

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

27 Citations (Scopus)

Abstract

Human action recognition and posture prediction aim to recognize and predict respectively the action and postures of persons in videos. They are both active research topics in computer vision community, which have attracted considerable attention from academia and industry. They are also the precondition for intelligent interaction and human-computer cooperation, and they help the machine perceive the external environment. In the past decade, tremendous progress has been made in the field, especially after the emergence of deep learning technologies. Hence, it is necessary to make a comprehensive review of recent developments. In this paper, firstly, we attempt to present the background, and then discuss research progresses. Secondly, we introduce datasets, various typical feature representation methods, and explore advanced human action recognition and posture prediction algorithms. Finally, facing the challenges in the field, this paper puts forward the research focus, and introduces the importance of action recognition and posture prediction by taking interactive cognition in self-driving vehicle as an example.

Original languageEnglish
Pages (from-to)973-1001
Number of pages29
JournalTsinghua Science and Technology
Volume27
Issue number6
Early online date21 Jun 2022
DOIs
Publication statusPublished - 1 Dec 2022

Scopus Subject Areas

  • General

User-Defined Keywords

  • computer vision
  • human action recognition
  • human-computer cooperation
  • interactive cognition
  • posture prediction

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