Abstract
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.
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This work is supported by Beijing Natural Science Foundation (Grant no. L191004).
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Liang, X., Lu, M., Chen, T., Wu, Z., Yuan, F. (2021). The Design of an Intelligent Monitoring System for Human Action. In: Shi, S., Ye, L., Zhang, Y. (eds) Artificial Intelligence for Communications and Networks. AICON 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 356. Springer, Cham. https://doi.org/10.1007/978-3-030-69066-3_49
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