An Efficient Real-Time Video Object Segmentation Algorithm Based on Change Detection and Background Updating

This paper proposes an efficient video object segmentation algorithm based on change detection and background updating that can quickly extract the moving object from video sequence. Firstly, the change detection is used to analyze temporal information between successive frames to obtain the change region. Then, the combination of frame difference mask and background subtraction mask is adopted to acquire the initial object mask and further solve the uncovered background problem and still object problem. Moreover, the boundary refinement is introduced to overcome the shadow influence and residual background problem. Finally, objective evaluations of the proposed algorithm demonstrate that the spatial accuracy can be maintained above 95% for most normal cases.