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Tuesday, 05 October 2010 10:19

Analysis of motion dynamics represents one of the most important phases in smoke detection, since that phase is usually used as a filter, isolating candidate regions for further analysis, thus largely reducing the amount of processing needed for detection. Most of smoke detection algorithms use some form of motion or change detection as the first phase of detection, followed by other types of candidate regions analysis. Analysis of motion dynamics can also be used in verification phase for rejection of certain types of false alarms. Some articles containing analysis of motion dynamics in smoke detection are listed here:




B. U. Toreyin, Y. Dedeoglu, A. E. Cetin,

“Wavelet based real-time smoke detection in video”,

EUSIPCO ’05, 2005.



P. Piccinini, S. Calderara, R. Cucchiara,

"Reliable smoke detection system in the domains of image energy and color",

International Conference on Image Processing, 1376-1379, 2008.



DongKeun Kim, Yuan-Fang Wang,

"Smoke Detection in Video",

WRI World Congress on Computer Science and Information Engineering, Vol. 5, 759 - 763, 2009.



E. den Breejen, M. Breuers, F. Cremer, R. Kemp, M. Roos, K. Schutte, J. S. de Vries,

"Autonomous Forest Fire Detection",

AusWeb 2000, The Sixth Australian World Wide Web Conference, 167-181, 1998.



J. Fernández-Berni, R. Carmona-Galán, L. Carranza-González,

"A vision-based monitoring system for very early automatic detection of forest fires",

Modelling, Monitoring and Management of Forest Fires, WIT Press, 161-170, 2008.







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