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Fast Approximate Energy Minimization via Graph Cuts
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere while preserving sharpExpand
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Fast approximate energy minimization via graph cuts
In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function's smoothness term must only involveExpand
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A taxonomy and evaluation of dense two-frame stereo correspondence algorithms
Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done onExpand
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What Energy Functions Can Be Minimized via Graph Cuts?
In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such thatExpand
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Image indexing using color correlograms
We define a new image feature called the color correlogram and use it for image indexing and comparison. This feature distills the spatial correlation of colors, and is both effective and inexpensiveExpand
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Non-parametric Local Transforms for Computing Visual Correspondence
We propose a new approach to the correspondence problem that makes use of non-parametric local transforms as the basis for correlation. Non-parametric local transforms rely on the relative orderingExpand
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Computing visual correspondence with occlusions using graph cuts
Several new algorithms for visual correspondence based on graph cuts have recently been developed. While these methods give very strong results in practice, they do not handle occlusions properly.Expand
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What energy functions can be minimized via graph cuts?
  • V. Kolmogorov, R. Zabih
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 28 May 2002
In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such thatExpand
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  • PDF
Multi-camera Scene Reconstruction via Graph Cuts
We address the problem of computing the 3-dimensional shape of an arbitrary scene from a set of images taken at known viewpoints. Multi-camera scene reconstruction is a natural generalization of theExpand
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A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation. It has been knownExpand
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