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Motion Segmentation and Matting by Graph Cut
Abstract
Given a video sequence, obtaining accurate layer segmentation and alpha matting is very important for video representation, analysis, compression, and synthesis. By assuming that a scene can be approximately described by multiple planar or surface regions, this chapter describes a robust approach to automatically detect the region clusters and perform accurate layer segmentation for the scene. The approach starts from optical flow field or small corresponding seed regions and applies a clustering approach to estimate the layer number and support regions. Then, it uses graph cut algorithm combined with a general occlusion constraint over multiple frames to solve pixel assignment over multiple frames to obtain more accurate segmentation boundary and identify the occluded pixels. For the non-textured ambiguous regions, an alpha matting technique is further used to refine the segmentation and resolve the ambiguities by determining proper alpha values for the foreground and background, respectively. Based on the alpha mattes, the foreground object can be transferred into the other video sequence to generate a virtual video. The author’s experiments show that the proposed approach is effective and robust for both the challenging real and synthetic sequences.
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