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 interframe 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 intraframe 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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Gu, I. Y. H., Gui, V., & Xu, Z. (2006). Video segmentation using joint space-time-range adaptive mean shift. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4261 LNCS, pp. 740–748). Springer Verlag. https://doi.org/10.1007/11922162_85
Mendeley helps you to discover research relevant for your work.