Real-time robust background subtraction under rapidly changing illumination conditions
Image and Vision Computing
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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. Therst 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