@inproceedings{05b333e0926e4446ac956c976edda3e3,
title = "Visual surveillance using deep reinforcement learning",
abstract = "Visual surveillance aims a robust detection of foreground objects, and traditional algorithms usually use a background model image. A current is compared with the background model image. In this paper, we present a visual surveillance algorithm, which determines the parameters in Vibe using deep reinforcement learning. We apply DQN to determine three parameters in Vibe algorithm. We present a policy model which is composed of encoder and decoder type network. Experimental results shows the feasibility of the presented algorithm.",
keywords = "BGS, Deep learning, GAN, Segmentation, Visual surveillance",
author = "Choi, \{Keong Hun\} and Ha, \{Jong Eun\}",
note = "Publisher Copyright: {\textcopyright} 2020 Institute of Control, Robotics, and Systems - ICROS.; 20th International Conference on Control, Automation and Systems, ICCAS 2020 ; Conference date: 13-10-2020 Through 16-10-2020",
year = "2020",
month = oct,
day = "13",
doi = "10.23919/ICCAS50221.2020.9268429",
language = "English",
series = "International Conference on Control, Automation and Systems",
publisher = "IEEE Computer Society",
pages = "289--291",
booktitle = "2020 20th International Conference on Control, Automation and Systems, ICCAS 2020",
}