Journal cover Journal topic
Proceedings of the ICA
Journal topic
Volume 1
Proc. Int. Cartogr. Assoc., 1, 116, 2018
https://doi.org/10.5194/ica-proc-1-116-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Proc. Int. Cartogr. Assoc., 1, 116, 2018
https://doi.org/10.5194/ica-proc-1-116-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  16 May 2018

16 May 2018

RJMCMC based Text Placement to Optimize Label Placement and Quantity

Guillaume Touya and Thibaud Chassin Guillaume Touya and Thibaud Chassin
  • Univ. Paris-Est, LASTIG COGIT, IGN, ENSG, F-94160 Saint-Mande, France

Keywords: label placement, optimization, RJMCMC, cartography

Abstract. Label placement is a tedious task in map design, and its automation has long been a goal for researchers in cartography, but also in computational geometry. Methods that search for an optimal or nearly optimal solution that satisfies a set of constraints, such as label overlapping, have been proposed in the literature. Most of these methods mainly focus on finding the optimal position for a given set of labels, but rarely allow the removal of labels as part of the optimization. This paper proposes to apply an optimization technique called Reversible-Jump Markov Chain Monte Carlo that enables to easily model the removal or addition during the optimization iterations. The method, quite preliminary for now, is tested on a real dataset, and the first results are encouraging.

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