Left is much better Left is slightly better No difference Right is slightly better Right is much better Figure 1: Comparing the abstraction quality of two stipple illustrations (left ∼15k and right ∼4k points) to an input image taken from our user study. We use this relative information to derive values for the absolute perceived abstraction quality of stippled representations.
We investigate how the perceived abstraction quality of computer-generated illustrations is related to the number of primitives (points and small lines) used to create them. Since it is difficult to find objective functions that quantify the visual quality of such illustrations, we propose an approach to derive perceptual models from a user study. By gathering comparative data in a crowdsourcing user study and employing a paired comparison model, we can reconstruct absolute quality values. Based on an exemplary study for stippling, we show that it is possible to model the perceived quality of stippled representations based on the properties of an input image. The generalizability of our approach is demonstrated by comparing models for different stippling methods. By showing that our proposed approach also works for small lines, we demonstrate its applicability toward quantifying different representational drawing elements. Our results can be related to Weber-Fechner's law from psychophysics and indicate a logarithmic relationship between number of rendering primitives in an illustration and the perceived abstraction quality thereof.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.