Action recognition system for security monitoring

Chao Yang; Dongyue Chen; Zhiming Xu

doi:10.1117/12.2626689

16 December 2021 Action recognition system for security monitoring

Chao Yang, Dongyue Chen, Zhiming Xu

Proceedings Volume 12153, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2021); 121530A (2021) https://doi.org/10.1117/12.2626689
Event: International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2021), 2021, Sanya, China

Abstract

In terms of security detection, security personnel often need to find potential dangerous events in time, although there are many monitoring equipment that can monitor behavior at any time. However, the real-time performance of monitoring equipment is not strong enough. Therefore, this paper proposes a novel action detection method suitable for violent action detection. In this method, the common camera is used as the data acquisition equipment, and the human skeleton structure is obtained by using the algorithm of object detection and pose estimation. Finally, it is recognized by graph convolution neural network. In addition, TensorRT acceleration technology is used in object detection and pose estimation algorithm, which further improves the real-time performance of action recognition and detection algorithm. Through the detection of the actual environment, it shows that the algorithm has good real-time performance and can be widely used in security monitoring.

Citation Download Citation

Chao Yang, Dongyue Chen, and Zhiming Xu "Action recognition system for security monitoring", Proc. SPIE 12153, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2021), 121530A (16 December 2021); https://doi.org/10.1117/12.2626689

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