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28
Factoring Algorithm for Counting the Number of (s,t)Mincuts of Each Size
, 1997
"... : An efficient family of methods to evaluate network reliability is the class of factoring algorithms. Their efficiency is due to the use of reliabilitypreserving reductions (for instance, seriesparallel ones). In this work, we follow a similar approach for the problem of counting the (s; t)mincu ..."
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: An efficient family of methods to evaluate network reliability is the class of factoring algorithms. Their efficiency is due to the use of reliabilitypreserving reductions (for instance, seriesparallel ones). In this work, we follow a similar approach for the problem of counting the (s; t)mincuts
P³ & beyond: Solving energies with higher order cliques
 IN COMPUTER VISION AND PATTERN RECOGNITION
, 2007
"... In this paper we extend the class of energy functions for which the optimal αexpansion and αβswap moves can be computed in polynomial time. Specifically, we introduce a class of higher order clique potentials and show that the expansion and swap moves for any energy function composed of these pote ..."
Abstract

Cited by 102 (17 self)
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of these potentials can be found by minimizing a submodular function. We also show that for a subset of these potentials, the optimal move can be found by solving an stmincut problem. We refer to this subset as the P n Potts model. Our results enable the use of powerful move making algorithms i.e. αexpansion and αβ
MAP Estimation of SemiMetric MRFs via Hierarchical Graph Cuts
"... We consider the task of obtaining the maximum a posteriori estimate of discrete pairwise random fields with arbitrary unary potentials and semimetric pairwise potentials. For this problem, we propose an accurate hierarchical move making strategy where each move is computed efficiently by solving an ..."
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Cited by 16 (4 self)
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an stMINCUT problem. Unlike previous move making approaches, e.g. the widely used αexpansion algorithm, our method obtains the guarantees of the standard linear programming (LP) relaxation for the important special case of metric labeling. Unlike the existing LP relaxation solvers, e.g. interior
P³ & Beyond: Move Making Algorithms for Solving Higher Order Functions
, 2008
"... In this paper we extend the class of energy functions for which the optimal αexpansion and αβswap moves can be computed in polynomial time. Specifically, we introduce a novel family of higher order clique potentials and show that the expansion and swap moves for any energy function composed of the ..."
Abstract

Cited by 4 (0 self)
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of these potentials can be found by minimizing a submodular function. We also show that for a subset of these potentials, the optimal move can be found by solving an stmincut problem. We refer to this subset as the Pn Potts model. Our results enable the use of powerful αexpansion and αβswap move making algorithms
Graph Cuts for Minimizing Robust Higher Order Potentials
"... Energy functions defined on higher order cliques can model complex interactions between groups of random variables. They have the capability of modelling the rich statistics of natural scenes which can be used for many applications in computer vision. However, these energies are seldom used in pract ..."
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Cited by 5 (3 self)
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show that energy functions containing such potentials can be solved using the expansion and swap move algorithms for approximate energy minimization. Specifically, we prove that the optimal swap and expansion moves for energy functions composed of these potentials can be computed by solving a stmincut
Efficiently Solving Dynamic Markov Random Fields using Graph Cuts
 IN: IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV
, 2005
"... In this paper we present a fast new fully dynamic algorithm for the stmincut/maxflow problem. We show how this algorithm can be used to efficiently compute MAP estimates for dynamically changing MRF models of labelling problems in computer vision, such as image segmentation. Specifically, given th ..."
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Cited by 63 (9 self)
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the performance of our algorithm on one particular problem: the objectbackground segmentation problem for video and compare it with the best known stmincut algorithm. The results show that the dynamic graph cut algorithm is much faster than its static counterpart and enables real time image segmentation
Improved Moves for Truncated Convex Models
"... We consider the problem of obtaining the approximate maximum a posteriori estimate of a discrete random field characterized by pairwise potentials that form a truncated convex model. For this problem, we propose an improved stMINCUT based move making algorithm. Unlike previous move making approache ..."
Abstract

Cited by 21 (3 self)
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We consider the problem of obtaining the approximate maximum a posteriori estimate of a discrete random field characterized by pairwise potentials that form a truncated convex model. For this problem, we propose an improved stMINCUT based move making algorithm. Unlike previous move making
1 The stConnectedness Problem for a Fibonacci Graph
"... Abstract: The paper presents a method for the solution of the stconnectedness problem for a Fibonacci graph. It is shown that this problem has a polynomial time complexity. The number of mincuts of a Fibonacci graph is computed. ..."
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Abstract: The paper presents a method for the solution of the stconnectedness problem for a Fibonacci graph. It is shown that this problem has a polynomial time complexity. The number of mincuts of a Fibonacci graph is computed.
Improved Moves for Truncated Convex Models
 In NIPS
"... We consider the problem of obtaining the approximate maximum a posteriori estimate of a discrete random field characterized by pairwise potentials that form a truncated convex model. For this problem, we propose an improved stMINCUT based move making algorithm. Unlike previous move making approache ..."
Abstract

Cited by 4 (1 self)
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We consider the problem of obtaining the approximate maximum a posteriori estimate of a discrete random field characterized by pairwise potentials that form a truncated convex model. For this problem, we propose an improved stMINCUT based move making algorithm. Unlike previous move making
Dynamic Graph Cuts for Efficient Inference in Markov Random Fields
"... In this paper we present a fast new fully dynamic algorithm for the stmincut/maxflow problem. We show how this algorithm can be used to efficiently compute MAP solutions for certain dynamically changing MRF models in computer vision such as image segmentation. Specifically, given the solution of ..."
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Cited by 77 (3 self)
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In this paper we present a fast new fully dynamic algorithm for the stmincut/maxflow problem. We show how this algorithm can be used to efficiently compute MAP solutions for certain dynamically changing MRF models in computer vision such as image segmentation. Specifically, given the solution
Results 1  10
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28