Biologically-inspired robust motion segmentation using mutual information
Presents novel neuroscience inspired information theoretic approach to motion segmentation based on mutual information. New model of current findings in biological vision is presented and link established to existing motion segmentation algorithms. Comparative performance evaluation across four challenging datasets. Comparative performance evaluation against competing segmentation methods.
segmentation performance evaluation biologically-inspired vision background modelling surveillance