The complexity of recognizing polyhedral scenes
Journal of Computer and System Sciences - 26th IEEE Conference on Foundations of Computer Science, October 21-23, 1985
From local to global consistency
Artificial Intelligence
On the minimality and global consistency of row-convex constraint networks
Journal of the ACM (JACM)
Closure properties of constraints
Journal of the ACM (JACM)
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
Synthesizing constraint expressions
Communications of the ACM
Consistency and set intersection
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Making AC-3 an optimal algorithm
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Simple randomized algorithms for tractable row and tree convex constraints
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Set intersection and consistency in constraint networks
Journal of Artificial Intelligence Research
| Hi-index | 0.00 |
A binary cnnstraint network is tree convex if we can construct a tree for the domain of the variables so that for any constraint, no matter what value one variable takes, all the values allowed for the other variable form a subtree of the constructed tree. It is known that a tree convex network is globally consistent if it is path consistent. However, if a tree convex network is not path consistent, enforcing path consistency on it may not make it globally consistent. In this paper, we identify a subclass of tree convex networks which are locally chain convex and union closed. This class of problems can be made globally consistent by path consistency and thus is tractable. More interestingly, we also find that some scene labeling problems can be modeled by tree convex constraints in a natural and meaningful way.