Change Detection by Frequency Decomposition: Wave-Back
Fatih Porikli, Christopher R. Wren · 2005
We introduce a frequency decomposition based back-ground generation and subtraction method that explicitly harnesses the scene dynamics to improve segmentation. This allows us to correctly interpret scenes that would confound appearance-based algorithms by having high-variance background in the presence of low-contrast targets, specifically when the background pixels are well modeled as cyclostationary random processes. In other words, we can distinguish near-periodic temporal patterns induced by real-world physics: the motion of plants driven by wind, the action of waves on a beach, and the appearance of ro-tating objects. To capture the cyclostationary behavior of each pixel, we compute the frequency coefficients of the temporal variation of pixel intensity in moving windows. We maintain a background model that is composed of fre-quency coefficients, and we compare the background model with the current set of coefficients to obtain a distance map. To eliminate trail effect, we fuse the distance maps. 1