Video based wildfire detection at night

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...

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Bibliographic Details
Published in:Fire safety journal 2009-08, Vol.44 (6), p.860-868
Main Authors: Gunay, O, Tasdemir, K, Ugur Toreyin, B, Enis Cetin, A
Format: Article
Language:English
Subjects:
Active learning
Applied sciences
Biological and medical sciences
Building technical equipments
Buildings
Buildings. Public works
Computer vision
Decision fusion
Detection. Firefighting. Smoke control. Evacuation
Exact sciences and technology
Fire detection
Fire protection
Fundamental and applied biological sciences. Psychology
Least-mean-square methods
On-line learning
Phytopathology. Animal pests. Plant and forest protection
Weather damages. Fires
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Summary: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.
ISSN:0379-7112
DOI:10.1016/j.firesaf.2009.04.003