Flame detection method in video using covariance descriptors
Author
Habiboǧlu, Y.H.
Günay, Osman
Çetin, A. Enis
Date
2011Source Title
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Print ISSN
1520-6149
Publisher
IEEE
Pages
1817 - 1820
Language
English
Type
Conference PaperItem Usage Stats
205
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159
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Abstract
Video fire detection system which uses a spatio-temporal covariance matrix of video data is proposed. This system divides the video into spatio-temporal blocks and computes covariance features extracted from these blocks to detect fire. Feature vectors taking advantage of both the spatial and the temporal characteristics of flame colored regions are classified using an SVM classifier which is trained and tested using video data containing flames and flame colored objects. Experimental results are presented. © 2011 IEEE.
Keywords
covariance descriptorsfire detection
support vector machines
Covariance features
Descriptors
Feature vectors
fire detection
Fire detection systems
Flame detection
Spatio-temporal
Support vector
SVM classifiers
Temporal characteristics
Video data
Covariance matrix
Fire detectors
Speech communication
Support vector machines
Video recording
Signal detection
Permalink
http://hdl.handle.net/11693/28373Published Version (Please cite this version)
http://dx.doi.org/10.1109/ICASSP.2011.5946857Collections
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