• About
  • Policies
  • What is open access
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
      • View Item
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Flame detection method in video using covariance descriptors

      Thumbnail
      View / Download
      261.2 Kb
      Author
      Habiboǧlu, Y.H.
      Günay, Osman
      Çetin, A. Enis
      Date
      2011
      Source 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 Paper
      Item Usage Stats
      205
      views
      159
      downloads
      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 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
      Permalink
      http://hdl.handle.net/11693/28373
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/ICASSP.2011.5946857
      Collections
      • Department of Electrical and Electronics Engineering 3637
      Show full item record

      Related items

      Showing items related by title, author, creator and subject.

      • Thumbnail

        A multi-modal video analysis approach for car park fire detection 

        Verstockt, S.; Hoecke, S. V.; Beji, T.; Merci, B.; Gouverneur, B.; Çetin, A. Enis; Potter, P. D.; Walle, R. V. D. (Elsevier, 2013)
        In this paper a novel multi-modal flame and smoke detector is proposed for the detection of fire in large open spaces such as car parks. The flame detector is based on the visual and amplitude image of a time-of-flight ...
      • Thumbnail

        VOC gas leak detection using pyro-electric infrared sensors 

        Erden, Fatih; Soyer, E. B.; Toreyin, B. U.; Çetin, A. Enis (IEEE, 2010)
        In this paper, we propose a novel method for detecting and monitoring Volatile Organic Compounds (VOC) gas leaks by using a Pyro-electric (or Passive) Infrared (PIR) sensor whose spectral range intersects with the absorption ...
      • Thumbnail

        Birleşik sezim ve kestirim sistemlerinin gürültü ile geliştirilmesi 

        Akbay, Abdullah Başar; Gezici, Sinan (IEEE, 2014-04)
        Belirli koşullar altında, optimal olmayan bazı sezici ve kestiricilerin performansını girdilerine gürültü ekleyerek geliştirmek mümkündür. Bu çalışmada, birleşik bir sezim ve kestirim sisteminin gürültü eklenerek geliştirilmesi ...

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartments

      My Account

      Login

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 1771
      © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy