Traditional and recent approaches in background modeling for foreground detection: An overview

Background modeling for foreground detection is often used in different applications to model the background and then detect the moving objects in the scene like in video surveillance. The last decade witnessed very significant publications in this field. Furthermore, several surveys can be found in the literature but none of them addresses an overall review in this field. So, the purpose of this paper is to provide a complete survey of the traditional and recent approaches. First, we categorize the different approaches found in the literature. We have classified them in terms of the mathematical models used and we have discussed them in terms of the critical situations that they claim to handle. Furthermore, we present the available resources, datasets and libraries. Then, we conclude with several promising directions for future research.