@article{ref1,
title="Video based wildfire detection at night",
journal="Fire safety journal",
year="2009",
author="Günay, Osman and Taşdemir, Kasım and Uğur Töreyin, B. and Enis Çetin, A.",
volume="44",
number="6",
pages="860-868",
abstract="There has been an increasing interest in the study of video based fire detection algorithms as video based surveillance systems become widely available for indoor and outdoor monitoring applications. A novel method explicitly developed for video based detection of wildfires at night (in the dark) is presented in this paper. The method comprises four sub-algorithms: (i) slow moving video object detection, (ii) bright region detection, (iii) detection of objects exhibiting periodic motion, and (iv) a sub-algorithm interpreting the motion of moving regions in video. Each of these sub-algorithms characterizes an aspect of fire captured at night by a visible range PTZ camera. Individual decisions of the sub-algorithms are combined together using a least-mean-square (LMS) based decision fusion approach, and fire/nofire decision is reached by an active learning method.<p /><p>Language: en</p>",
language="en",
issn="0379-7112",
doi="10.1016/j.firesaf.2009.04.003",
url="http://dx.doi.org/10.1016/j.firesaf.2009.04.003"
}