Results 1  10
of
1,693,924
Comparison of energy minimization algorithms for highly connected graphs
 IN PROC. ECCV
, 2006
"... Algorithms for discrete energy minimization play a fundamental role for lowlevel vision. Known techniques include graph cuts, belief propagation (BP) and recently introduced treereweighted message passing (TRW). So far, the standard benchmark for their comparison has been a 4connected gridgraph ..."
Abstract

Cited by 28 (2 self)
 Add to MetaCart
Algorithms for discrete energy minimization play a fundamental role for lowlevel vision. Known techniques include graph cuts, belief propagation (BP) and recently introduced treereweighted message passing (TRW). So far, the standard benchmark for their comparison has been a 4connected grid
A Free Energy Minimization Algorithm for Decoding and Cryptanalysis
, 1995
"... An algorithm is derived for inferring a binary vector s given noisy observations of Asmodulo 2, where A is a binary matrix. Here, the binary vector is replaced by a vector of probabilities, optimized by free energy minimization. Experiments on the inference of the state of a linear feedback shift re ..."
Abstract

Cited by 14 (9 self)
 Add to MetaCart
An algorithm is derived for inferring a binary vector s given noisy observations of Asmodulo 2, where A is a binary matrix. Here, the binary vector is replaced by a vector of probabilities, optimized by free energy minimization. Experiments on the inference of the state of a linear feedback shift
An Experimental Comparison of MinCut/MaxFlow Algorithms for Energy Minimization in Vision
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2001
"... After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in lowlevel vision. The combinatorial optimization literature provides many mincut/maxflow algorithms with different polynomial time compl ..."
Abstract

Cited by 1313 (53 self)
 Add to MetaCart
After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in lowlevel vision. The combinatorial optimization literature provides many mincut/maxflow algorithms with different polynomial time
A Fast and Exact Energy Minimization Algorithm for Cycle MRFs
"... The presence of cycles gives rise to the difficulty in performing inference for MRFs. Handling cycles efficiently would greatly enhance our ability to tackle general MRFs. In particular, for dual decomposition of energy minimization (MAP inference), using cycle subproblems leads to a much tighter re ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
relaxation than using trees, but solving the cycle subproblems turns out to be the bottleneck. In this paper, we present a fast and exact algorithm for energy minimization in cycle MRFs, which can be used as a subroutine in tackling general MRFs. Our method builds on junctiontree message passing, with a
Fast approximate energy minimization via graph cuts
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2001
"... 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 involve pairs of pixels. We propose two algorithms that use graph cuts to compute a local minimum even when v ..."
Abstract

Cited by 2121 (61 self)
 Add to MetaCart
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 involve pairs of pixels. We propose two algorithms that use graph cuts to compute a local minimum even when
Convergent Treereweighted Message Passing for Energy Minimization
 ACCEPTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (PAMI), 2006. ABSTRACTACCEPTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (PAMI)
, 2006
"... Algorithms for discrete energy minimization are of fundamental importance in computer vision. In this paper we focus on the recent technique proposed by Wainwright et al. [33] treereweighted maxproduct message passing (TRW). It was inspired by the problem of maximizing a lower bound on the energy ..."
Abstract

Cited by 488 (16 self)
 Add to MetaCart
Algorithms for discrete energy minimization are of fundamental importance in computer vision. In this paper we focus on the recent technique proposed by Wainwright et al. [33] treereweighted maxproduct message passing (TRW). It was inspired by the problem of maximizing a lower bound
A comparative study of energy minimization methods for Markov random fields
 IN ECCV
, 2006
"... One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with some quantity such as depth or texture. While many such problems can be elegantly expressed in the language of Markov Ran ..."
Abstract

Cited by 416 (36 self)
 Add to MetaCart
One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with some quantity such as depth or texture. While many such problems can be elegantly expressed in the language of Markov
What energy functions can be minimized via graph cuts?
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2004
"... 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 that the minimum cut on the graph also minimizes the energy. Yet, because these graph constructions are co ..."
Abstract

Cited by 1048 (23 self)
 Add to MetaCart
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 that the minimum cut on the graph also minimizes the energy. Yet, because these graph constructions
An Algorithm for Total Variation Minimization and Applications
, 2004
"... We propose an algorithm for minimizing the total variation of an image, and provide a proof of convergence. We show applications to image denoising, zooming, and the computation of the mean curvature motion of interfaces. ..."
Abstract

Cited by 626 (8 self)
 Add to MetaCart
We propose an algorithm for minimizing the total variation of an image, and provide a proof of convergence. We show applications to image denoising, zooming, and the computation of the mean curvature motion of interfaces.
Randomized Gossip Algorithms
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 2006
"... Motivated by applications to sensor, peertopeer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join a ..."
Abstract

Cited by 532 (5 self)
 Add to MetaCart
and old nodes leave the network. Algorithms for such networks need to be robust against changes in topology. Additionally, nodes in sensor networks operate under limited computational, communication, and energy resources. These constraints have motivated the design of “gossip ” algorithms: schemes which
Results 1  10
of
1,693,924