Visual Computing

University of Konstanz
Proceedings of the Symposium on Non-Photorealistic Animation and Rendering

Quantifying Visual Abstraction Quality for Stipple Drawings

M. Spicker, F. Hahn, T. Lindemeier, D. Saupe, O. Deussen
Best Paper Award Expressive 2017

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


We investigate how the perceived abstraction quality of stipple illustrations is related to the number of points used to create them. Since it is difficult to find objective functions that quantify the visual quality of such illustrations, we gather comparative data by a crowdsourcing user study and employ a paired comparison model to deduce absolute quality values. Based on this study we show that it is possible to predict the perceived quality of stippled representations based on the properties of an input image. Our results are related to Weber--Fechner's law from psychophysics and indicate a logarithmic relation between numbers of points and perceived abstraction quality. We give guidance for the number of stipple points that is typically enough to represent an input image well.

Note: In addition to the related work presented in the paper, a very recent study on digital stippling by Martín et al. can be found here.


  acmid      = {3092923},
  address    = {New York, NY, USA},
  articleno  = {8},
  author     = {M. Spicker and F. Hahn and T. Lindemeier and D. Saupe and O. Deussen},
  booktitle  = {Proceedings of the Symposium on Non-Photorealistic Animation and Rendering},
  doi        = {10.1145/3092919.3092923},
  isbn       = {978-1-4503-5081-5},
  keywords   = {non-photorealistic rendering, perception, quantitative evaluation, stippling, user study, visual abstraction},
  location   = {Los Angeles, California},
  numpages   = {10},
  pages      = {8:1--8:10},
  publisher  = {ACM},
  series     = {NPAR '17},
  title      = {Quantifying Visual Abstraction Quality for Stipple Drawings},
  url        = {},
  year       = {2017},

Supplemental Material

Paper (.pdf, 5.1 MB) Presentation (.pptx, 10.0 MB) Data (Images) (.zip, 124.3 MB) Data (User study) (.zip, 1.1 MB)