Linear programming 1: introduction
Linear programming 1: introduction
A combinatorial algorithm minimizing submodular functions in strongly polynomial time
Journal of Combinatorial Theory Series B
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fully combinatorial algorithm for submodular function minimization
Journal of Combinatorial Theory Series B
Discrete Applied Mathematics
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Energy Minimization via Graph Cuts: Settling What is Possible
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Minimizing Nonsubmodular Functions with Graph Cuts-A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient belief propagation for higher-order cliques using linear constraint nodes
Computer Vision and Image Understanding
Optimizing Binary MRFs with Higher Order Cliques
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Robust Higher Order Potentials for Enforcing Label Consistency
International Journal of Computer Vision
Transformation of General Binary MRF Minimization to the First-Order Case
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic word alignment under the L0-norm
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Statistical priors for efficient combinatorial optimization via graph cuts
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Efficient belief propagation with learned higher-order markov random fields
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Constructing free-energy approximations and generalized belief propagation algorithms
IEEE Transactions on Information Theory
MAP estimation via agreement on trees: message-passing and linear programming
IEEE Transactions on Information Theory
| Hi-index | 0.00 |
We present a technique to handle computer vision problems inducing models with very high order terms - in fact terms of maximal order. Here we consider terms where the cost function depends only on the number of variables that are assigned a certain label, but where the dependence is arbitrary. Applications include image segmentation with a histogram-based data term [28] and the recently introduced marginal probability fields [31]. The presented technique makes use of linear and integer linear programming. We include a set of customized cuts to strengthen the formulations.