Ghosting suppression for incremental principal component pursuit algorithms
In video background modeling, ghosting occurs when an object that belongs to the background is assigned to the foreground. In the context of Principal Component Pursuit, this usually occurs when a moving object occludes a high contrast background object, a moving object suddenly stops, or a stationary object suddenly starts moving. Based on a previously developed incremental PCP method, we propose a novel algorithm that uses two simultaneous background estimates based on observations over the previous n1 and n2 (n1 C n2) frames in order to identify and diminish the ghosting effect. Our computational results show that the proposed method greatly improves both the subjective quality and accuracy as determined by the F-measure.