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A novel stochastic searching scheme based on the Monte Carlo optimization is presented for polygonal approximation (PA) problem. We propose to combine the split-and-merge based local optimization and the Monte Carlo sampling, to give an efficient stochastic optimization scheme. Our approach, in essence, is a well-designed Basin-Hopping scheme, which performs stochastic hopping among the reduced energy...
In this paper, we propose an example-based facial sketch hallucination approach. Given a face image, its sketch image will be automatically hallucinated by learning from a training set, which includes a lot of face images and their corresponding sketch images. Our algorithm involves three stages. In the first stage which is called ??feature extracting??, we create the feature pyramid for each face...
In this paper, two new energy functions are presented to handle the slanted plane. First, the gradient information is used to get the initial disparity in a local energy function. Second, a global energy function is incorporating segment geometric constraints. To overcome the fronto-parallel model errors, the segment adjacent segments cooperative optimization is used to infer the unreliable pixel...
In this paper, we proposed a novel approach to image completion for overlapping chromosomes. In our system, only given missing regions, the task can be performed automatically without human intervention. We address the problem of image completion for overlapping chromosomes in the context of a discrete global optimization problem. In order to reconstruct the original chromosome image as faithfully...
The aim of the stereo matching is to get the accurate disparity. But for the slanted and low textured plane, the ambiguity is increased. To get the more accurate disparity, most constraints are applied. In this paper, the statistical probability method (SPT) is applied to inferring disparity. The reliable confidence (RC) based on the SPT measures how the pixel disparity is reliable. The unreliable...
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