Method for predicting behavior of substation workers based on generative confrontation network

Yuanjing Deng; Zhi Yang; Bin Liu; Shenghe Wang; Yun Gao; Jie Huang; Binbin Zhao; Mengxuan Li

doi:10.1117/12.2615165

15 October 2021 Method for predicting behavior of substation workers based on generative confrontation network

Yuanjing Deng, Zhi Yang, Bin Liu, Shenghe Wang, Yun Gao, Jie Huang, Binbin Zhao, Mengxuan Li

Proceedings Volume 11933, 2021 International Conference on Neural Networks, Information and Communication Engineering; 119332N (2021) https://doi.org/10.1117/12.2615165
Event: 2021 International Conference on Neural Networks, Information and Communication Engineering, 2021, Qingdao, China

Abstract

A method for predicting abnormal behaviors of substation workers based on video scenes and using generative confrontation networks to integrate global and local information is proposed. In the substation, this method can be used to issue timely warnings to the transportation and inspection personnel that may trigger dangerous actions during the operation, so as to provide an important guarantee for the life and safety of the transportation and inspection personnel. The human behavior prediction task aims to predict future behavior video frames based on a given behavior video frame. Considering that the human behavior video contains not only relatively stable scene information, but also time-varying and complex human behavior information, this method first uses a global generation confrontation network to generate video scenes and rough human contours; then uses local generation confrontation Network to further optimize the details of human behavior in the video. Experiments show that, compared with the existing methods that only use a single model to achieve pixel-level behavior prediction, the method of combining global and local generation proposed in this paper can better capture the spatial appearance and the timing dynamics of humans in the video.

Citation Download Citation

Yuanjing Deng, Zhi Yang, Bin Liu, Shenghe Wang, Yun Gao, Jie Huang, Binbin Zhao, and Mengxuan Li "Method for predicting behavior of substation workers based on generative confrontation network", Proc. SPIE 11933, 2021 International Conference on Neural Networks, Information and Communication Engineering, 119332N (15 October 2021); https://doi.org/10.1117/12.2615165

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KEYWORDS

Video

Data modeling

Performance modeling

Image enhancement

Safety

Video processing

Feature extraction

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