Savcı M. M., Yildirim Y., Saygili G., Töreyin B. U.

44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom, 12 - 17 May 2019, pp.8310-8314 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icassp.2019.8683666
  • City: Brighton
  • Country: United Kingdom
  • Page Numbers: pp.8310-8314
  • Keywords: fire detection, compressed domain, macroblock type, H.264/AVC
  • Istanbul Technical University Affiliated: Yes


In this paper, we propose a compressed domain fire detection algorithm using macroblock types and Markov Model in H. 264 video. Compressed domain method does not require decoding to pixel domain, instead a syntax parser extracts syntax elements which are only available in compressed domain. Our method extracts only macroblock type and corresponding macroblock address information. Markov model with fire and non-fire models are evaluated using offlinetrained data. Our experiments show that the algorithm is able to detect and identify fire event in compressed domain successfully, despite a small chunk of data is used in the process.