@inproceedings{fc6522eb9ad74dd68ab49c78010f36bb,
title = "A novel smoke detection algorithm based on Fast Self-tuning background subtraction",
abstract = "The smoke detection in remote video surveillance is of great importance in forest fire prevention since smoke usually appears before fire. In order to solve this problem, we proposed a novel smoke detection algorithm based on fast self-tuning background subtraction segmentation and judgments of smoke analysis. First, a self-tuning background algorithm is utilized on the source image to segment the candidate smoke regions, which overcomes the drawbacks in color-based and motion-based segmentation methods. Then the static and dynamic judgments of smoke are applied on the candidate smoke regions to identify the smoke region. Experiment results demonstrate that our algorithm performs well on detecting smoke in remote video surveillance while achieving robustness to the change of environment.",
keywords = "Additional judgments of smoke, Self-tuning background subtraction, Smoke detection",
author = "Shuai Li and Bo Wang and Ranran Dong and Zhiqiang Zhou and Sun Li",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 28th Chinese Control and Decision Conference, CCDC 2016 ; Conference date: 28-05-2016 Through 30-05-2016",
year = "2016",
month = aug,
day = "3",
doi = "10.1109/CCDC.2016.7531596",
language = "English",
series = "Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3539--3543",
booktitle = "Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016",
address = "United States",
}