An adaptive real-time background subtraction and moving shadows detection

This paper presents a statistical adaptive realtime background subtraction algorithm that is very robust to moving shadows and dynamic scene environment. The algorithm enhances the previously developed method reported in [4] by adding adaptation of modeling correspond to dynamic background using adaptive brightness and color distortion. In addition, we propose a novel "vivacity factor" to measure activities of foreground objects. It is used to delay the adaptation rate for the area of often-occurred moving foregrounds. Our method provides a solution to real-time moving object and shadow detection in dynamic background scene from video stream. We also develop the learning-rate control mechanism that was not addressed by most background subtraction algorithms.