Habiboǧlu, Y.H.Günay, OsmanÇetin, A. Enis2016-02-082016-02-0820111520-6149http://hdl.handle.net/11693/28373Date of Conference: 22-27 May 2011Video 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.Englishcovariance descriptorsfire detectionsupport vector machinesCovariance featuresDescriptorsFeature vectorsfire detectionFire detection systemsFlame detectionSpatio-temporalSupport vectorSVM classifiersTemporal characteristicsVideo dataCovariance matrixFire detectorsSpeech communicationSupport vector machinesVideo recordingSignal detectionConference Paper10.1109/ICASSP.2011.5946857