Metric 3D Structure in Visualizations

Abstract

A large body of results on the characteristics of human spatial vision suggests that space perception is distorted. Recent studies indicate that the geometry of visual space is best understood as affine. If this is the case, it has far-reaching implications on how 3D visualizations can be successfully employed. For instance, all attempts to build visualization systems where users are expected to discover relations based on Euclidean distances or shapes will be ineffective. Since visualization can, and sometimes does, employ all possible types of depth information and because the results from vision research usually concentrates on one or two such types, three experiments were performed under near-optimal viewing conditions. The aim of the experiments was two-fold: to test whether the earlier findings generalize to shape perception under near-optimal viewing conditions and to get a sense of the size of the error under such conditions. The results show that the findings do generalize and that the errors are large. The implications of these results for successful visualizations are discussed.