here."/>

Visual Computing

University of Konstanz
ACM Transactions on Applied Perception

Quantifying Visual Abstraction Quality for Computer-Generated Illustrations

M. Spicker, F. Götz-Hahn, T. Lindemeier, D. Saupe, O. Deussen
Teaser of Quantifying Visual Abstraction Quality for Computer-Generated Illustrations

We ask you to rate which Stippling representation (left or right) you consider to better represent an image (center).

Material

Paper (.pdf, 9.7MB)

Abstract

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 towards 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.

Note: This is an extended journal version of our 2017 NPAR paper which can be found here.

Gallery

Comparison of models for different stippling settings (constant and variable point sizes). The dashed black lines indicate the models’ means, the colored area around it depict the 95% confidence intervals. Dots are abstraction scores for the evaluation study on a different stimulus, shown as inset. Image copyright Domingo Martín Perandrés.

BibTeX

@article{Spicker2019QuantifyingVisualAbstraction,
  acmid      = {3301414},
  address    = {New York, NY, USA},
  articleno  = {5},
  author     = {M. Spicker, F. Götz-Hahn, T. Lindemeier, D. Saupe, O. Deussen},
  doi        = {10.1145/3301414},
  issn       = {1544-3558},
  issue_date = {February 2019},
  journal    = {ACM Transactions on Applied Perception},
  keywords   = {Visual abstraction, non-photorealistic rendering, perception, stippling, user study},
  month      = {feb},
  number     = {1},
  numpages   = {20},
  pages      = {5:1--5:20},
  publisher  = {ACM},
  title      = {Quantifying Visual Abstraction Quality for Computer-Generated Illustrations},
  url        = {http://graphics.uni-konstanz.de/publikationen/Spicker2019QuantifyingVisualAbstraction},
  volume     = {16},
  year       = {2019}
}