Dynamic object recognition through static background removal in case of remote sensing data acquired by a single video camera

Scene analysis and description is the ultimate goal of many video surveillance systems. Change detection, which is used in many vision systems, is one of the fundamental techniques for various security tasks, such as video surveillance. In this work we will deal with the methodology that would apply when we have a video that was shot with a stationary camera. It will be a static picture as the background and a group of moving objects. The main concept of change detection is to define a background and detect foreground regions as differences between the defined background and a current observation. In order to recognize objects that are in motion to remove the background using a specific methodology. Reporting is performed by sequentially removing the background characteristics, which makes the method more adaptable to the changing environment. Change detection methods are categorized into two methods: those for stationary cameras and those for moving cameras. Furthermore, the utilization of picture detection methods with minimally controlled equipment in some frameworks is a difficult issue for any case in practice. The method requires a small amount of computational time to detect the presence of moving objects for a video surveillance and is based on geometry features mainly.