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In this paper, we propose a novel segmentation approach for stereo images using the high-order energy optimization, which utilizes the disparity maps and statistical information of stereo images to enrich the high-order potential functions. To the best of our knowledge, our approach is the first one to formulate the problem of stereo segmentation as a(More)
In this paper, we propose a novel saliency-aware stereo images segmentation approach using the high-order energy items, which utilizes the disparity map and statistical information of stereo images to enrich the high-order potentials. To the best of our knowledge, our approach is first one to formulate the automatic stereo cut as the high-order energy(More)
—A novel superpixel extraction algorithm using a higher-order energy optimization framework is proposed in this paper. We first adopt the k-means clustering technique to quickly get an initial superpixel result. Then a higher-order energy function is employed to optimize and refine these initial superpixels. We use a more general higher-order energy(More)
A novel energy minimization method for general higher-order binary energy functions is proposed in this paper. We first relax a discrete higher-order function to a continuous one, and use the Taylor expansion to obtain an approximate lower-order function, which is optimized by the quadratic pseudo-boolean optimization (QPBO) or other discrete optimizers.(More)
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