Viewpoint Optimization for 3D Graph Drawings
Year: 2025
Type: article
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.
Source: Computer Graphics Forum
DOI: 10.1111/cgf.70127
Authors: S. van Wageningen, T. Mchedlidze, A. Telea
Institution: Utrecht University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,710
OpenAlex ID: W4410679042