TY - JOUR
T1 - A Survey of Human Action Recognition and Posture Prediction
AU - Ma, Nan
AU - Wu, Zhixuan
AU - Cheung, Yiu Ming
AU - Guo, Yuchen
AU - Gao, Yue
AU - Li, Jiahong
AU - Jiang, Beijyan
N1 - The authors wish to thank Dian'en Zhang and Wenjuan Li from Beijing Union University, Beijing, China. We really thank anonymous reviewers' constructive suggestions. This work was supported by the National Natural Science Foundation of China (Nos. 61871038 and 61931012), the Premium Funding Project for Academic Human Resources Development of Beijing Union University (No. BPHR2020AZ02), and the Generic Pre-research Program of the Equipment Development Department in Military Commission (No. 41412040302).
Publisher Copyright:
© 1996-2012 Tsinghua University Press.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - 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.
AB - 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.
KW - computer vision
KW - human action recognition
KW - human-computer cooperation
KW - interactive cognition
KW - posture prediction
UR - http://www.scopus.com/inward/record.url?scp=85133680058&partnerID=8YFLogxK
U2 - 10.26599/TST.2021.9010068
DO - 10.26599/TST.2021.9010068
M3 - Journal article
AN - SCOPUS:85133680058
SN - 1007-0214
VL - 27
SP - 973
EP - 1001
JO - Tsinghua Science and Technology
JF - Tsinghua Science and Technology
IS - 6
ER -