Multi-layered Background Modeling for Complex Environment Surveillance

Abstract

Many background models have been proposed to adapt to "illumination changes" and "dynamic changes" such as swaying motion of tree branches. However, the problem of background maintenance in complex environment, where foreground objects pass in front of stationary objects which cease moving, is still far from being completely solved. To address this problem, we propose a framework for multi-layered background modeling, in which we conserve the background models for stationary objects hierarchically in addition to the one for the initial background. To realize this framework, we also propose a spatio-temporal background model based on the similarity in the intensity changes among pixels. Experimental results on complex scenes, such as a bus stop and an intersection, show that our proposed method can adapt to both appearances and disappearances of stationary objects thanks to the multi-layered background modeling framework.