Background Subtraction under Sudden Illumination Changes

Abstract

Robust background subtraction under sudden illuminationchanges is a challenging problem. In this paper, wepropose an approach to address this issue, which combinesthe Eigenbackground algorithm together with a statisticalillumination model. The rst algorithm is used to give arough reconstruction of the input frame, while the secondone improves the foreground segmentation. We introduce anonline spatial likelihood model by detecting reliable backgroundand foreground pixels. Experimental results illustratethat our approach achieves consistently higher accuracycompared to several state-of-the-art algorithms