Video Background Segmentation Using Adaptive Background Models

This paper proposes an adaptive background model which combines the advantages of both Eigenbackground and pixel-based gaussian models. This method exploits the illumination changes by Eigenbackground. Moreover, it can detect, the chroma changes and remove shadow pixels using gaussian models. An adaptively strategy is used to integrate two models. A binary graph cut is used to implement the foreground/background segmentation by developing our data term and smooth term. We validate our method on indoor videos and test it on the benchmark video. Experiments demonstrate our method's efficiency.