Browsing by Subject "SVM classifiers"

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    Flame detection method in video using covariance descriptors
    (IEEE, 2011) Habiboǧlu, Y.H.; Günay, Osman; Çetin, A. Enis
    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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    Real-time wildfire detection using correlation descriptors
    (IEEE, 2011) Habiboğlu, Y. Hakan; Günay, Osman; Çetin, A. Enis
    A video based wildfire detection system that based on spatio-temporal correlation descriptors is developed. During the initial stages of wildfires smoke plume becomes visible before the flames. The proposed method uses background subtraction and color thresholds to find the smoke colored slow moving regions in video. These regions are divided into spatio-temporal blocks and correlation features are extracted from the blocks. Property sets that represent both the spatial and the temporal characteristics of smoke regions are used to form correlation descriptors. An SVM classifier is trained and tested with descriptors obtained from video data containing smoke and smoke colored objects. Experimental results are presented. © 2011 EURASIP.