Abstract:
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 d...Show MoreMetadata
Abstract:
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 offline-trained 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.
Published in: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Date of Conference: 12-17 May 2019
Date Added to IEEE Xplore: 17 April 2019
ISBN Information:
ISSN Information:
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- IEEE Keywords
- Index Terms
- Video Compression ,
- Fire Detection ,
- Fire Model ,
- Pixel Domain ,
- False Negative ,
- Convolutional Neural Network ,
- Deep Neural Network ,
- Wavelet ,
- Object Detection ,
- Transition Probabilities ,
- Deep Convolutional Neural Network ,
- Temporal Information ,
- Window Length ,
- Deep Architecture ,
- Video Analysis ,
- Convolutional Neural Network Architecture ,
- Temporal Processing ,
- Object Tracking ,
- Deep Neural Network Architecture ,
- Previous Frame ,
- Firing Process
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Video Compression ,
- Fire Detection ,
- Fire Model ,
- Pixel Domain ,
- False Negative ,
- Convolutional Neural Network ,
- Deep Neural Network ,
- Wavelet ,
- Object Detection ,
- Transition Probabilities ,
- Deep Convolutional Neural Network ,
- Temporal Information ,
- Window Length ,
- Deep Architecture ,
- Video Analysis ,
- Convolutional Neural Network Architecture ,
- Temporal Processing ,
- Object Tracking ,
- Deep Neural Network Architecture ,
- Previous Frame ,
- Firing Process
- Author Keywords