Fire Detection Algorithms Using Multimodal ... - Bilkent University

CHAPTER 6. WILDFIRE DETECTION 85each incoming sample x. If the number is positive (negative), then the individualalgorithm decides that there is (not) smoke due to forest fire in the viewing rangeof the camera. Output values of decision functions express the confidence levelof each sub-algorithm. Higher the value, the more confident the algorithm.6.2.1 Detection of Slow Moving ObjectsVideo objects at far distances to the camera seem to move slower (px/sec) incomparison to the nearby objects moving at the same speed. Assuming thecamera is fixed, two background images, B fast (x, n) and B slow (x, n) correspondingto the scene with different update rates are estimated [9], [65], where x is thelocation of the pixel at frame number n.In [19] a background image B(x, n + 1) at time instant n + 1 is recursivelyestimated from the image frame I(x, n) and the background image B(x, n) of thevideo as follows:B(x, n + 1) =B(x, n){aB(x, n) + (1 − a)I(x, n) if x is stationaryif x is a moving pixel(6.1)where I(x, n) represent the intensity value of the pixel at location x in the n thvideo frame I, and a is a parameter between 0 and 1. Initially, B fast (x, 0) andB slow (x, 0) can be taken as I(x, 0). Stationary and moving pixel definitions aregiven in [19]. Background images B fast (x, n) and B slow (x, n) are updated as inEq. 6.1 with different update rates. In our implementation, B fast (x, n) is updatedat every frame and B slow (x, n) is updated once in a second with a = 0.7 and 0.9,respectively.Slow moving objects within the viewing range of the camera are detected bycomparing background images, B fast and B slow [83], [9], [65]. If there exists asubstantial difference between the two images for some period of time, then analarm for slow moving region is raised, and the region is marked.The decision value indicating the confidence level of the first sub-algorithm isdetermined by the difference between background images. The decision function