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Fast Approximate Energy Minimization via Graph Cuts
This work presents two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves, namely expansion moves and swap moves that allow important cases of discontinuity preserving energies.
Fast approximate energy minimization via graph cuts
This paper proposes two algorithms that use graph cuts to compute a local minimum even when very large moves are allowed, and generates a labeling such that there is no expansion move that decreases the energy.
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 on
Image indexing using color correlograms
Experimental evidence suggests that this new image feature called the color correlogram outperforms not only the traditional color histogram method but also the recently proposed histogram refinement methods for image indexing/retrieval.
Non-parametric Local Transforms for Computing Visual Correspondence
A new approach to the correspondence problem that makes use of non-parametric local transforms as the basis for correlation, which can result in improved performance near object boundaries when compared with conventional methods such as normalized correlation.
Computing visual correspondence with occlusions using graph cuts
This paper presents a new method which properly addresses occlusions, while preserving the advantages of graph cut algorithms, and gives experimental results for stereo as well as motion, which demonstrate that the method performs well both at detecting occlusion and computing disparities.
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
This work gives a precise characterization of what energy functions can be minimized using graph cuts, among the energy functions that can be written as a sum of terms containing three or fewer binary variables.
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
A set of energy minimization benchmarks are described and used to compare the solution quality and runtime of several common energy minimizations algorithms and a general-purpose software interface is provided that allows vision researchers to easily switch between optimization methods.
Multi-camera Scene Reconstruction via Graph Cuts
This paper addresses the problem of computing the 3-dimensional shape of an arbitrary scene from a set of images taken at known viewpoints by giving an energy minimization formulation of the multi-camera scene reconstruction problem.
Comparing images using color coherence vectors
It is shown that CCV’s can give superior results to color histogram-based methods for comparing images that incorporates spatial information, and to whom correspondence should be addressed tograms for image retrieval.