Robust Motion Detection via the Fuzzy Fusion of 6D Feature Space Decompositions

Abstract

A change detection framework which fuses both spatial and temporal data using fuzzy if-then rules is presented. Temporal data is used on a per-pixel basis to monitor the sequence for changes by employing a fuzzy codebook model. Spatial data is gathered using a fuzzy multithresholding algorithm that decomposes the RGB color space into three color pair histograms. This system is found to be robust to noise and allows the algorithm to process successfully even when the underlying sequences result in under-segmentation of the spatial data.