A Genetic Algorithm Optimising Control Point Placement for Edge Bundling

Ryosuke Saga, Tomoki Yoshikawa, Ken Wakita, Ken Sakamoto, Gerald Schaefer, Tomoharu Nakashima

Abstract

This paper describes a novel approach of edge bundling that employs a genetic algorithm (GA) to optimise the placement of control points. Edge bundling is a useful technique to reduce visual clutter and a number of model-based edge bundling approaches have been introduced in the literature. However, these do not attempt to optimise aesthetic rules directly. Differently from them, our approach assumes that edge bundling is regarded as an optimisation problem for aesthetic rules. To solve this problem, we present an GA-based algorithm where gene representation defines control points of edges in order to allow flexibility and the fitness function is defined based on quantitative criteria for edge bundling. Experimental results using a visualisation of a Japanese airline map demonstrates the feasibility of our proposed method and its usability.

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Paper Citation


in Harvard Style

Saga R., Yoshikawa T., Wakita K., Sakamoto K., Schaefer G. and Nakashima T. (2020). A Genetic Algorithm Optimising Control Point Placement for Edge Bundling.In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, ISBN 978-989-758-402-2, pages 217-222. DOI: 10.5220/0008983202170222


in Bibtex Style

@conference{ivapp20,
author={Ryosuke Saga and Tomoki Yoshikawa and Ken Wakita and Ken Sakamoto and Gerald Schaefer and Tomoharu Nakashima},
title={A Genetic Algorithm Optimising Control Point Placement for Edge Bundling},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},
year={2020},
pages={217-222},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008983202170222},
isbn={978-989-758-402-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,
TI - A Genetic Algorithm Optimising Control Point Placement for Edge Bundling
SN - 978-989-758-402-2
AU - Saga R.
AU - Yoshikawa T.
AU - Wakita K.
AU - Sakamoto K.
AU - Schaefer G.
AU - Nakashima T.
PY - 2020
SP - 217
EP - 222
DO - 10.5220/0008983202170222