Abstract
Background models are used for object detection in many computer vision algorithms. In this article, we propose a novel background modeling method based on frequency for spatially varying and time repetitive textured background. The local Fourier transform is applied to construct a pixel-wise representation of local frequency components. We apply our method for object detection in moving background conditions. Experimental results of our frequency-based background model are evaluated both qualitatively and quantitatively. (c) 2012 Elsevier B.V. All rights reserved.