Video segmentation based on spatial and temporal information

The paper presents a morphological spatio-temporal segmentation method, which is based on a new similarity measure. This similarity measure considers jointly spatial and temporal information and consists therefore of two terms. The first term minimizes the displaced frame difference, considering the affine motion model. By the second term the spatial homogeneity of the luminance values of every region is maximized. The procedure toward complete segmentation consists of three steps: joint marker extraction, boundary decision, and motion-based region fusion. By incorporating spatial and temporal information simultaneously, we can obtain visually meaningful segmentation results. Simulation results demonstrates the efficiency of the proposed method.