An effective multi-stage background generation algorithm

In this paper we present a new background generation algorithm and show experimental results aimed at assessing its performance comparatively with respect to two other representative approaches. The algorithm is able to extract a stationary background from a short bootstrap sequence in which moving objects can also be present. The method works with pixel-wise temporal statistics and consists of three subsequent stages. The first two try to isolate for each pixel the stationary background process from the possible foreground processes due to the moving objects covering the pixel, thus voting the background process temporal median as the good background value. The third stage completes the background generation by means of a non-parametric statistical model of the temporal camera noise, inferred from the statistics computed in the previous stage.