Flame detection method in video using covariance descriptors

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Flame detection method in video using covariance descriptors.pdf (261.23 KB)

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2011

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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.

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2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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IEEE

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Keywords

covariance descriptors, fire 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

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http://hdl.handle.net/11693/28373

Published Version (Please cite this version)

http://dx.doi.org/10.1109/ICASSP.2011.5946857

Collections

Scholarly Publications - Electrical and Electronics Engineering

Language

English

Type

Conference Paper