An adaptive real-time background subtraction and moving shadows detection

Abstract

The 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 by T. Horprascrt et al. (see Proc. IEEE ICCV'99 Frame-rate Workshop, 1999) by adding adaptation of the model corresponding to a dynamic background using adaptive brightness and color distortion. In addition, we propose a novel "vivacity factor" to measure the activities of foreground objects. It is used to delay the adaptation rate for the area of often-occurring moving foregrounds. Our method provides a solution to real-time moving object and shadow detection in the dynamic background scene of a video stream. We also develop the learning-rate control mechanism that is not addressed by most background subtraction algorithms