Video Segmentation using Joint Space-Time-Range Adaptive Mean Shift

Video segmentation has drawn increasing interest in multimedia applications. This paper proposes a novel joint space-time-range domain adaptive mean shift filter for video segmentation. In the proposed method, segmentation of moving/static objects/background is obtained through inter-frame mode-matching in consecutive frames and motion vector mode estimation. Newly appearing objects/regions in the current frame due to new foreground objects or uncovered background regions are segmented by intra-frame mode estimation. Simulations have been conducted to several image sequences, and results have shown the effectiveness and robustness of the proposed method. Further study is continued to evaluate the results

Video Segmentation using Joint Space-Time-Range Adaptive Mean Shift

Video segmentation has drawn increasing interest in multimedia applications. This paper proposes a novel joint space-time-range domain adaptive mean shift filter for video segmentation. In the proposed method, segmentation of moving/static objects/background is obtained through inter-frame mode-matching in consecutive frames and motion vector mode estimation. Newly appearing objects/regions in the current frame due to new foreground objects or uncovered background regions are segmented by intra-frame mode estimation. Simulations have been conducted to several image sequences, and results have shown the effectiveness and robustness of the proposed method. Further study is continued to evaluate the results