Adaptive, Region-based, Layered Background Model for Target Tracking

Background subtraction is a method frequently used in target detection and tracking applications. In this paper, we present a new approach to background subtraction that relies on a two-layer background model. This approach uses a single intensity model for all the pixels rather than separate models for individual pixel, by exploiting the spatial dependency of pixels. It models the background without modeling the foreground, and treats background updating and tracking as tightly integrated dynamic processes rather than consecutive static modules. This method can handle illumination changes, permanent changes to the background, and targets that stop moving and later start moving again. Example results are presented