REAL-TIME VIDEO OBJECT SEGMENTATION ALGORITHM BASED ON CHANGE DETECTION AND BACKGROUND UPDATING

This paper proposes an efficient real-time video object segmentation algorithm based on change detection and back-ground updating. The basic idea is to use the change detection technique to analyze temporal information between successive frames for extracting the change region. Then, the combination of frame difference mask and background subtraction mask is employed to quickly acquire the initial object mask and further solve the uncovered back-ground problem and still object problem. Moreover, the novel hierarchical boundary refinement is introduced to overcome the shadow influence and residual background problem. The objective evaluations of the proposed algorithm demonstrate that the spatial accuracy can be maintained above 95% for most normal cases.