Pixelated Image Abstraction with Integrated User Constraints

Timothy Gerstner, Doug DeCarlo, Marc Alexa, Adam Finkelstein, Yotam Gingold, Andrew Nealen
Computers & Graphics, Volume 37, Number 5, August 2013.
(This article is the expansion of an NPAR conference paper.)

Input photographs and semi-automatically created pixel art.


We present an automatic method that can be used to abstract high resolution images into very low resolution outputs with reduced color palettes in the style of pixel art. Our method simultaneously solves for a mapping of features and a reduced palette needed to construct the output image. The results are an approximation to the results generated by pixel artists. We compare our method against the results of two naive methods common to image manipulation programs, as well as the hand-crafted work of pixel artists. Through a formal user study and interviews with expert pixel artists we show that our results offer an improvement over the naive methods. By integrating a set of manual controls into our algorithm, we give users the ability to add constraints and incorporate their own choices into the iterative process.

Paper: PDF (11M) | PDF (2M)

Tim Gerstner's thesis: PDF (21 MB)

Source Code: ZIP (200 KB)

Guide to the Interface PDF (400 KB)

Executables: macOS ZIP (1 MB) | Windows ZIP (1 MB)


  title   = {Pixelated image abstraction with integrated user constraints},
  author  = {Timothy Gerstner and Doug DeCarlo and Marc Alexa and Adam Finkelstein and Yotam Gingold and Andrew Nealen},
  journal = {Computers \& Graphics},
  year    = {2013},
  volume  = {37},
  number  = {5},
  pages   = {333--347},
  issn    = {0097-8493},
  doi     = {http://dx.doi.org/10.1016/j.cag.2012.12.007},
  url     = {http://www.sciencedirect.com/science/article/pii/S0097849313000046},