Emergent Mind

Constrained Boundary Labeling

(2402.12245)
Published Feb 19, 2024 in cs.CG and cs.CC

Abstract

Boundary labeling is a technique used to label dense sets of feature points in an illustration. It involves placing labels along a rectangular boundary box and connecting each label with its corresponding feature using non-crossing leader lines. Although boundary labeling is well-studied, semantic constraints on the labels have not been investigated thoroughly. In this paper, we consider grouping and ordering constraints for boundary labeling: Grouping constraints enforce that all labels in a group are placed consecutively on the boundary, and ordering constraints enforce a partial order over the labels. We show that finding an admissible labeling for labels of uniform size that can be placed on fixed candidate positions on two opposite sides of the boundary is NP-complete. Furthermore, we show that it is also weakly NP-hard to find an admissible labeling for non-uniform labels that can slide along one side of the boundary. However, we obtain polynomial-time algorithms in the one-sided setting for either fixed candidate positions or uniform-height labels. Finally, we experimentally confirm that our approach has also practical relevance.

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