Background Modeling for Fire Detection

A video-based fire detection system for outdoor surveillance should be capable of continuous operation under various environmental conditions, such as the change of background illumination and variation of background objects. In this paper, we present a novel background modeling method in which a nonparametric statistical test is utilized for effective and robust detection of stationary background corners. The practical value of the method is demonstrated with an oil-field surveillance system where it is applied for video-based fire detection. The validation results and analysis indicate that the proposed method is able to cope with small occlusions and periodic motions.

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