TY - GEN
T1 - The Design of an Intelligent Monitoring System for Human Action
AU - Liang, Xin
AU - Lu, Mingfeng
AU - Chen, Tairan
AU - Wu, Zhengliang
AU - Yuan, Fangzhou
N1 - Publisher Copyright:
© 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2021
Y1 - 2021
N2 - Now the monitoring equipment such as cameras has been widely used in social life. In order to solve the problem that the current monitoring equipment relies on manual screening for the recognition of abnormal human action and is not time-efficient and automatic, an intelligent monitoring system for human action is designed in this paper. The system uses object detection, classification and interactive recognition algorithm in deep learning, combines 3D coordinate system transformation and attention mechanism model. It can recognize the local human hand actions, head pose and a variety of global human interaction actions in the current environment in real time and automatically, and judge whether they are abnormal or special actions. The system has high accuracy and high speed, and has been tested successfully in laboratory environment with good effect. It can also reduce labor costs, improve the efficiency of security monitoring, and provide help for solving urban security issues.
AB - Now the monitoring equipment such as cameras has been widely used in social life. In order to solve the problem that the current monitoring equipment relies on manual screening for the recognition of abnormal human action and is not time-efficient and automatic, an intelligent monitoring system for human action is designed in this paper. The system uses object detection, classification and interactive recognition algorithm in deep learning, combines 3D coordinate system transformation and attention mechanism model. It can recognize the local human hand actions, head pose and a variety of global human interaction actions in the current environment in real time and automatically, and judge whether they are abnormal or special actions. The system has high accuracy and high speed, and has been tested successfully in laboratory environment with good effect. It can also reduce labor costs, improve the efficiency of security monitoring, and provide help for solving urban security issues.
KW - Action recognition
KW - Deep learning
KW - Intelligent monitoring
KW - Security issues
UR - http://www.scopus.com/inward/record.url?scp=85104475450&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-69066-3_49
DO - 10.1007/978-3-030-69066-3_49
M3 - Conference contribution
AN - SCOPUS:85104475450
SN - 9783030690656
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 558
EP - 570
BT - Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings
A2 - Shi, Shuo
A2 - Ye, Liang
A2 - Zhang, Yu
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2020
Y2 - 19 December 2020 through 20 December 2020
ER -
