Color quantization by dynamic programming and principal analysis
ACM Transactions on Graphics (TOG)
Reproducing color images using custom inks
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artistic Vision: painterly rendering using computer vision techniques
NPAR '02 Proceedings of the 2nd international symposium on Non-photorealistic animation and rendering
Stylization and abstraction of photographs
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Color image quantization for frame buffer display
SIGGRAPH '82 Proceedings of the 9th annual conference on Computer graphics and interactive techniques
Suggestive contours for conveying shape
ACM SIGGRAPH 2003 Papers
ACM SIGGRAPH 2006 Papers
Apparent ridges for line drawing
ACM SIGGRAPH 2007 papers
Computer-Generated Papercutting
PG '07 Proceedings of the 15th Pacific Conference on Computer Graphics and Applications
TurboPixels: Fast Superpixels Using Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM SIGGRAPH 2011 papers
IEEE Transactions on Signal Processing
IEEE Transactions on Image Processing
On spatial quantization of color images
IEEE Transactions on Image Processing
NPAR '12 Proceedings of the Symposium on Non-Photorealistic Animation and Rendering
NPAR '12 Proceedings of the Symposium on Non-Photorealistic Animation and Rendering
Generating knitting patterns from a sketch: a CSP approach
Proceedings of the Symposium on Computational Aesthetics
Introduction: Foreword to the special section on expressive graphics
Computers and Graphics
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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.