Let M = (A, <, P) where (A, <) is a linear ordering and P denotes a finite sequence of monadic predicates on A. We show that if A contains an interval of order type or -, an...
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...
In this paper we generalize the contraction method, originally proposed by Elgot and Rabin and later extended by Carton and Thomas, from labeled linear orderings to colored determ...
Markov Random Fields (MRFs) are ubiquitous in lowlevel computer vision. In this paper, we propose a new approach to the optimization of multi-labeled MRFs. Similarly to -expansion...
—Data trees are trees in which each node, besides carrying a label from a finite alphabet, also carries a data value infinite domain. They have been used as an abstraction mode...