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Kyushu Institute of Technology
Kyushu Institute of Technology
Kyushu Institute of Technology
抄録
One of the important roles of a camera surveillance system is to detect abnormal human actions or events. In this study, we propose a method of abnormal human actions/events detection method using Generative Adversarial Nets (GAN). In anomaly action detection, the main problem is that the image data of abnormal human actions is more difficult to obtain than normal human actions. To solve this difficulty, we use only normal human action data in the employed training network and those actions not recognized as normal are judged as abnormal. Experimental results show effectiveness of the proposed method.
内容記述
The 2021 International Conference on Artificial Life and Robotics (ICAROB 2021), January 21-24, 2021, Higashi-Hiroshima (オンライン開催に変更)
雑誌名
Proceedings of International Conference on Artificial Life & Robotics (ICAROB2021)
ページ
287 - 290
発行年
2021-01-22
出版者
ALife Robotics
ISSN
2435-9157
ISBN
978-4-9908350-6-4
DOI
https://doi.org/10.5954/ICAROB.2021.OS14-3
権利
Copyright (c) The 2021 International Conference on Artificial Life and Robotics (ICAROB2021)
Abnormal Human Action Detection Based on GAN
ICAROB2021_OS14-3.pdf
(325.8KB)
