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In this paper we select the inner contour and outer contour of the target object, and then apply watershed algorithm to divide the region between the inner contour and the outer contour into series of smaller regions. Each smaller region is regarded as a node, and the small regions contains of the inner contour are regarded as the source s, and the small regions contains of the outer contour are regarded...
This paper presents an approximate belief propagation algorithm that replaces outgoing messages from a node with the averaged outgoing message and propagates messages from a low resolution graph to the original graph hierarchically. The proposed method reduces the computational time by half or two-thirds and reduces the required amount of memory by 60% compared with the standard belief propagation...
GMM based algorithms have become the de facto standard for background subtraction in video sequences, mainly because of their ability to track multiple background distributions, which allows them to handle complex scenes including moving trees, flags moving in the wind etc. However, it is not always easy to determine which distributions of the mixture belong to the background and which distributions...
Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical...
Approximate solutions to labelling problems can be found using binary graph cuts and either the ??-?? expansion or ??-?? swap algorithms. In some specific cases, an exact solution can be computed by constructing a multilabel graph. However, in many practical applications the multilabel graph construction is infeasible due to its excessively large memory requirements. In this work, we expand the concept...
This paper copes with the approximate minimization of Markovian energy with pairwise interactions. We extend previous approaches that rely on graph-cuts and move making techniques. For this purpose, a new move is introduced that permits us to perform better approximate optimizations. Some experiments show that very good local minima are obtained while keeping the memory usage low.
Several new algorithms for stereo matching based on graph cuts have recently been developed for pixel-labeling tasks such as depth. Such problem can be expressed as Markov random fields, yet the resulting energy minimization problems have been widely viewed as intractable. In this paper, we describe energy minimization based on graph cuts. The data term of energy function adopts three different approaches...
Interactive segmentation is often performed on images that have been stored on disk (e.g., a medical image server) for some time prior to user interaction. We propose to use this time to perform an offline precomputation of the segmentation prior to user interaction that significantly decreases the amount of user time necessary to produce a segmentation. Knowing how to effectively precompute the segmentation...
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