Video based wildfire detection at night

Date
2009-05-06
Advisor
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Source Title
Fire Safety Journal
Print ISSN
0379-7112
Electronic ISSN
Publisher
ELSEVIER
Volume
44
Issue
6
Pages
860 - 868
Language
English
Type
Article
Journal Title
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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.

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Keywords
Active learning, Computer vision, Decision fusion, Fire detection, Least-mean-square methods, On-line learning
Citation
Published Version (Please cite this version)