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A novel sub-Markov random walk (subRW) algorithm with label prior is proposed for seeded image segmentation, which can be interpreted as a traditional random walker on a graph with added auxiliary nodes. Under this explanation, we unify the proposed subRW and other popular random walk (RW) algorithms. This unifying view will make it possible for(More)
We propose a novel interactive cosegmentation method using global and local energy optimization. The global energy includes two terms: 1) the global scribbled energy and 2) the interimage energy. The first one utilizes the user scribbles to build the Gaussian mixture model and improve the cosegmentation performance. The second one is a global constraint,(More)
In this paper, we present a supervoxel generation algorithm based on partially absorbing random walks to get more accurate supervoxels in these regions. A novel spatial-temporal framework is introduced by making full use of the appearance features and motion cues, which effectively exploits the temporal consistency in the video sequence. Moreover, we build(More)
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