Target-Tracking Based Early Fire Smoke Detection in Video

The paper proposed a target-tracking based fire smoke detection method for early fire-alarming system at large or open space. The method utilizes an improved Gaussian mixture model positioning algorithm, an efficient target tracking algorithm as well as three effective static and dynamic smoke visual features: brightness consistency, motion accumulation and spread. Finally, an algorithm combined temporal and spatial information to assess the fire alarm algorithm is implemented by considering the performance requirements of the fire-alarming system. Experimental results show that the method has low time complexity and is able to rule out the major interference sources.

[1]  A. Enis Çetin,et al.  Signal recovery from wavelet transform maxima , 1994, IEEE Trans. Signal Process..

[2]  P. KaewTrakulPong,et al.  An Improved Adaptive Background Mixture Model for Real-time Tracking with Shadow Detection , 2002 .

[3]  Zheng Xiaolong.  Smoke Dynamic Features Based Real-Time Fire Detection , 2008 .

[4]  A. Enis Çetin,et al.  Real-time fire and flame detection in video , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[5]  Chao-Ho Chen,et al.  An early fire-detection method based on image processing , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[6]  W. Eric L. Grimson,et al.  Using adaptive tracking to classify and monitor activities in a site , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[7]  S. Noda,et al.  Fire detection in tunnels using an image processing method , 1994, Proceedings of VNIS'94 - 1994 Vehicle Navigation and Information Systems Conference.

[8]  Thou-Ho Chen,et al.  An intelligent real-time fire-detection method based on video processing , 2003, IEEE 37th Annual 2003 International Carnahan Conference onSecurity Technology, 2003. Proceedings..