Abstract
Object-based segmentation of image sequences is one of the issues often arise in the world of video processing and communications. In this paper, a robust semiautomatic video object segmentation scheme is proposed. To facilitate users defining the initial object contour efficiently and accurately, an improved intelligent scissors is proposed by trading off the accuracy of original intelligent scissors and the simplicity of bounding box. To avoid the accumulated errors during object tracking, video sequence is firstly decomposed into video clips according to the rigidity of video object and the motion complexity. Then a snake-based bi-directional tracking is utilized to interpolate the video object planes (VOPs) of successive frames. Experimental results demonstrate that it can achieve better spatial accuracy and temporal coherency than COST211 AM, with about 10-22% improvement of spatial accuracy and almost the same temporal coherency.
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