Beham, M., Herzner, W., Gröller, E., & Kehrer, J. (2014). Cupid: Cluster-based Exploration of Geometry Generators with Parallel Coordinates and Radial Trees. IEEE Transactions on Visualization and Computer Graphics, 20(12), 1693–1702. https://doi.org/10.1109/tvcg.2014.2346626
IEEE Transactions on Visualization and Computer Graphics
Number of Pages:
Institute of Electrical and Electronics Engineers (IEEE)
Software; Computer Graphics and Computer-Aided Design; Computer Vision and Pattern Recognition; Signal Processing; 3D shape analysis; radial trees; hierarchical clustering; illustrative parallel coordinates; composite visualization
Geometry generators are commonly used in video games and evaluation systems for computer vision to create geometric shapes such as terrains, vegetation or airplanes. The parameters of the generator are often sampled automatically which can lead to many similar or unwanted geometric shapes. In this paper, we propose a novel visual exploration approach that combines the abstract parameter space of the geometry generator with the resulting 3D shapes in a composite visualization. Similar geometric shapes are first grouped using hierarchical clustering and then nested within an illustrative parallel coordinates visualization. This helps the user to study the sensitivity of the generator with respect to its parameter space and to identify invalid parameter settings. Starting from a compact overview representation, the user can iteratively drill-down into local shape differences by clicking on the respective clusters. Additionally, a linked radial tree gives an overview of the cluster hierarchy and enables the user to manually split or merge clusters. We evaluate our approach by exploring the parameter space of a cup generator and provide feedback from domain experts.