Viewpoint Optimization for 3D Graph Drawings
Loading...
Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
Graph drawings using a node-link metaphor and straight edges are widely used to represent and understand relational data. While such drawings are typically created in 2D, 3D representations have also gained popularity. When exploring 3D drawings, finding viewpoints that help understanding the graph's structure is crucial. Finding good viewpoints also allows using the 3D drawings to generate good 2D graph drawings. In this work, we tackle the problem of automatically finding high-quality viewpoints for 3D graph drawings. We propose and evaluate strategies based on sampling, gradient descent, and evolutionary-inspired meta-heuristics. Our results show that most strategies quickly converge to high-quality viewpoints within a few dozen function evaluations, with meta-heuristic approaches showing robust performance regardless of the quality metric.
Description
CCS Concepts: Human-centered computing → Graph drawings; Computing methodologies → Genetic algorithms; Neural networks
@article{10.1111:cgf.70127,
journal = {Computer Graphics Forum},
title = {{Viewpoint Optimization for 3D Graph Drawings}},
author = {Wageningen, Simon van and Mchedlidze, Tamara and Telea, Alexandru},
year = {2025},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.70127}
}