Moving object detection with background model based on spatio-temporal texture

Background subtraction is a common method for detecting moving objects, but it is yet a difficult problem to distinguish moving objects from backgrounds when these backgrounds change significantly. Hence, we propose a method for detecting moving objects with a background model that covers dynamic changes in backgrounds utilizing a spatio-temporal texture named “Space-Time Patch”, which describes motion and appearance, whereas conventional textures describe appearance only. Our experimental results show the proposed method outperforms one conventional method in three scenes: in an outdoor scene where leaves and branches of a tree are waving in intermittent wind, in an indoor scene where ceiling lights are turned on and off frequently, and in an escalator scene beside a window facing outdoors where some passengers are leaning over the hand-rail.