A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual reconstruction
Algorithms for clustering data
Algorithms for clustering data
Introduction to algorithms
Parallel and Deterministic Algorithms from MRFs: Surface Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Occlusions, Discontinuities, and Epipolar Lines in Stereo
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
On Implementing Push-Relabel Method for the Maximum Flow Problem
Proceedings of the 4th International IPCO Conference on Integer Programming and Combinatorial Optimization
Kona: A Multi-junction Detector Using Minimum Description Length Principle
EMMCVPR '97 Proceedings of the First International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Smoothness in Layers: Motion segmentation using nonparametric mixture estimation.
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Quantitative Measures of Change based on Feature Organization: Eigenvalues and Eigenvectors
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Markov Random Fields with Efficient Approximations
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Maximum-Flow Formulation of the N-Camera Stereo Correspondence Problem
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A constant factor approximation algorithm for a class of classification problems
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Stereo Without Epipolar Lines: A Maximum-Flow Formulation
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
Approximation algorithms for the metric labeling problem via a new linear programming formulation
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
An efficient algorithm for image segmentation, Markov random fields and related problems
Journal of the ACM (JACM)
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
A Framework for Automatic Adaptation of Tunable Distributed Applications
Cluster Computing
Isophotes Selection and Reaction-Diffusion Model for Object Boundaries Estimation
International Journal of Computer Vision
Perceptual organization based computational model for robust segmentation of moving objects
Computer Vision and Image Understanding
What Energy Functions Can Be Minimized via Graph Cuts?
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Optimal Net Surface Problems with Applications
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
A New Algorithm for Energy Minimization with Discontinuities
EMMCVPR '99 Proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
A Discrete/Continuous Minimization Method in Interferometric Image Processing
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
An Experimental Comparison of Min-cut/Max-flow Algorithms for Energy Minimization in Vision
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Segmentation of Dynamic N-D Data Sets via Graph Cuts Using Markov Models
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Bayesian Models for Finding and Grouping Junctions
EMMCVPR '99 Proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Markov Random Fields with Efficient Approximations
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation Given Partial Grouping Constraints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Approximate classification via earthmover metrics
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
A Linear Programming Approach to Max-Sum Problem: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Approximate Labeling via Graph Cuts Based on Linear Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object segmentation using graph cuts based active contours
Computer Vision and Image Understanding
Dynamic Graph Cuts for Efficient Inference in Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstructing relief surfaces
Image and Vision Computing
Limited view CT reconstruction and segmentation via constrained metric labeling
Computer Vision and Image Understanding
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
A simple corner orientation detector
ISCGAV'08 Proceedings of the 8th conference on Signal processing, computational geometry and artificial vision
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Semi-supervised Segmentation Based on Non-local Continuous Min-Cut
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
L0-Norm and Total Variation for Wavelet Inpainting
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Benchmarking Image Segmentation Algorithms
International Journal of Computer Vision
Exact solution of permuted submodular minsum problems
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Nugget-cut: a segmentation scheme for spherically- and elliptically-shaped 3D objects
Proceedings of the 32nd DAGM conference on Pattern recognition
Diffusion algorithms and structural recognition optimization problems
Cybernetics and Systems Analysis
Compression and denoising using l0-norm
Computational Optimization and Applications
Spectral clustering: A semi-supervised approach
Neurocomputing
Global Solutions of Variational Models with Convex Regularization
SIAM Journal on Imaging Sciences
Spectral clustering with discriminant cuts
Knowledge-Based Systems
Total variation minimization and a class of binary MRF models
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Approximating a class of classification problems
Efficient Approximation and Online Algorithms
An efficient and effective tool for image segmentation, total variations and regularization
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Segmentation of liver tumor using efficient global optimal tree metrics graph cuts
MICCAI'11 Proceedings of the Third international conference on Abdominal Imaging: computational and Clinical Applications
Computer Vision and Image Understanding
Computer Vision and Image Understanding
Accurate Junction Detection and Characterization in Natural Images
International Journal of Computer Vision
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We propose a method for segmenting gray-value images. By segmentation, we mean a map from the set of pixels to a small set of levels such that each connected component of the set of pixels with the same level forms a relatively large and "meaningful" region. The method finds a set of levels with associated gray values by first finding junctions in the image and then seeking a minimum set of threshold values that preserves the junctions. Then it finds a segmentation map that maps each pixel to the level with the closest gray value to the pixel data, within a smoothness constraint. For a convex smoothing penalty, we show the global optimal solution for an energy function that fits the data can be obtained in a polynomial time, by a novel use of the maximum-flow algorithm. Our approach is in contrast to a view in computer vision where segmentation is driven by intensity gradient, usually not yielding closed boundaries.