Learning Hatching for Pen-and-Ink Illustration of Surfaces

Evangelos Kalogerakis, Derek Nowrouzezahrai, Simon Breslav, Aaron Hertzmann
ACM Transactions on Graphics - to be presented at ACM SIGGRAPH (2012)

Abstract

This paper presents an algorithm for learning hatching styles from line drawings. An artist draws a single hatching illustration of a 3D object. Their strokes are analyzed to extract the following per-pixel properties: hatching level (hatching, cross-hatching, or no strokes), stroke orientation, spacing, intensity, length, and thickness. A mapping is learned from input features to these properties, using classification, regression, and clustering techniques. Then, a new illustration can be generated in the artist's style, as follows. First, given a new view of a 3D object, the learned mapping is applied to synthesize target stroke properties for each pixel. A new illustration is then generated by synthesizing hatching strokes according to the target properties.

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BIBTEX

@article{Kalogerakis:2011:mlhatching,
Author = {Evangelos Kalogerakis and Derek Nowrouzezahrai and Simon Breslav and Aaron Hertzmann},
Title = {Learning {H}atching for {P}en-and-{I}nk {I}llustration of {S}urfaces},
Journal = {ACM Transactions on Graphics},
Volume = {31},
Number = {1},
Year = {2011},
}
© Derek Nowrouzezahrai 2005 - 2012