Quantifying Visual Abstraction Quality for Stipple Drawings
M. Spicker, F. Hahn, T. Lindemeier, D. Saupe, and O. Deussen. Proceedings of the Symposium on Non-Photorealistic Animation and Rendering (NPAR), page 8:1-8:10. Association for Computing Machinery, (2017)
Abstract
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.
%0 Conference Paper
%1 spickerqantifying
%A Spicker, Marc
%A Hahn, Franz
%A Lindemeier, Thomas
%A Saupe, Dietmar
%A Deussen, Oliver
%B Proceedings of the Symposium on Non-Photorealistic Animation and Rendering (NPAR)
%D 2017
%E ACM,
%I Association for Computing Machinery
%K 2017 A04 A05 from:leonkokkoliadis sfbtrr161
%P 8:1-8:10
%T Quantifying Visual Abstraction Quality for Stipple Drawings
%U https://doi.org/http://dx.doi.org/10.1145/3092919.3092923
%X 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.
@inproceedings{spickerqantifying,
abstract = {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.},
added-at = {2020-02-26T15:02:39.000+0100},
author = {Spicker, Marc and Hahn, Franz and Lindemeier, Thomas and Saupe, Dietmar and Deussen, Oliver},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2be472071c70f71ad8fae9a06f8a586ba/sfbtrr161},
booktitle = {Proceedings of the Symposium on Non-Photorealistic Animation and Rendering (NPAR)},
editor = {ACM},
interhash = {a80ca8495d83aaf8f1e34898c12ad54c},
intrahash = {be472071c70f71ad8fae9a06f8a586ba},
keywords = {2017 A04 A05 from:leonkokkoliadis sfbtrr161},
pages = {8:1-8:10},
publisher = {Association for Computing Machinery},
timestamp = {2020-02-26T15:25:55.000+0100},
title = {Quantifying Visual Abstraction Quality for Stipple Drawings},
url = {https://doi.org/http://dx.doi.org/10.1145/3092919.3092923},
year = 2017
}
