We present a novel approach to background subtraction that is based on the
local shape of small image regions. In our approach, an image region centered
on a pixel is mod-eled using the local self-similarity descriptor. We aim at
obtaining a reliable change detection based on local shape change in an image
when foreground objects are moving. The method first builds a background model
and compares the local self-similarities between the background model and the
subsequent frames to distinguish background and foreground objects.
Post-processing is then used to refine the boundaries of moving objects.
Results show that this approach is promising as the foregrounds obtained are
com-plete, although they often include shadows.Comment: 4 pages, 5 figures, 3 tabl