Recursive Median Filter for Background Estimation and Foreground Segmentation in Surveillance Videos

Video cameras are widely used in surveillance systems; this offers the possibility of processing the captured images for automatic detection of events of interest that may arise in the scene. The present paper proposes a method for estimating the background and foreground segmentation in video surveillance using a recursive median filter and applying a temporal moving window in the number of frames to be analyzed, which provide more robustness against noise caused by changes in illumination and camera shake, limiting the increase in the computational cost of processing.