| Abstract |
Measures of dissimilarity of 3D models are necessary in a wide
range of applications such as geometry compression, simplification, and
3D model retrieval. In many cases a metric that models perceptual
dissimilarity is desirable. Recently, metrics for 3D models have been
evaluated in that respect using concepts such as just noticeable
differences, rankings, and others. We propose a simple experimental
setup for evaluating supra-threshold perception of 3D models in which
users select models at equal perceptual distance to given pairs of
models. We discuss the advantages of our approach and report the
results of a field study comparing six objective distance measures
applied to palettes of simplified reference models. We found that the
objective measures are biased, and generally image-based metrics
perform better than metrics based on the original 3D geometry. |