Background Extraction and Updating in Complex Traffic Scene

In this paper,a multilayer background model adapted to complex traffic scene is established. A random image subtraction method is adopted to obtain candidate background pixels. A method integrated with temporal and spatial statistics is used to build the background and the credibility of every pixel. The updating is implemented with feedback of object tracking results and shadows excluding,which contributes in fast background restoring when objects' moving status change,and detecting temporary static objects in the scene. Finally,Experiments prove that the algorithm presented in this paper is reliable in restoring real background timely and the veracity of object detection is improved.