Arc and path consistence revisited
Artificial Intelligence
The complexity of recognizing polyhedral scenes
Journal of Computer and System Sciences - 26th IEEE Conference on Foundations of Computer Science, October 21-23, 1985
Artificial intelligence (3rd ed.)
Artificial intelligence (3rd ed.)
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)
Constraints, consistency and closure
Artificial Intelligence
Constraint satisfaction over connected row-convex constraints
Artificial Intelligence
Synthesizing constraint expressions
Communications of the ACM
Consistency and set intersection
Eighteenth national conference on Artificial intelligence
Generating Semantic Descriptions From Drawings of Scenes With Shadows
Generating Semantic Descriptions From Drawings of Scenes With Shadows
An optimal coarse-grained arc consistency algorithm
Artificial Intelligence
Combinatorial auctions with structured item graphs
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Simple randomized algorithms for tractable row and tree convex constraints
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Making AC-3 an optimal algorithm
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Decomposing combinatorial auctions and set packing problems
Journal of the ACM (JACM)
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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 investigate the properties of some tree convex constraints under intersection and composition. As a result, we identify a sub-class of tree convex networks that are locally chain convex and strictly union closed. This class of problems can be made globally consistent by arc and path consistency and thus is tractable. Interestingly, we also find that some scene labeling problems can be modeled by tree convex constraints in a natural and meaningful way.