Subspace Shapes: Enhancing High-Dimensional Subspace Structures via Ambient Occlusion Shading

TL;DR

This paper investigates whether transforming high-dimensional data into 3D shaded visualizations improves human understanding and perception compared to traditional scatterplots, especially for cluster analysis.

Contribution

It demonstrates that 3D shaded displays are preferred by users and enhance the communication of spatial relationships and shapes in high-dimensional data visualization.

Findings

Users prefer shaded 3D displays over scatterplots after training.

3D displays better communicate spatial relationships and cluster shapes.

Shaded visualizations improve understanding of high-dimensional data.

Abstract

We test the hypothesis whether transforming a data matrix into a 3D shaded surface or even a volumetric display can be more appealing to humans than a scatterplot since it makes direct use of the innate 3D scene understanding capabilities of the human visual system. We also test whether 3D shaded displays can add a significant amount of information to the visualization of high-dimensional data, especially when enhanced with proper tools to navigate the various 3D subspaces. Our experiments suggest that mainstream users prefer shaded displays over scatterplots for visual cluster analysis tasks after receiving training for both. Our experiments also provide evidence that 3D displays can better communicate spatial relationships, size, and shape of clusters.