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E. Kalogerakis, D. Nowrouzezahrai, S. Breslav, A. Hertzmann, Learning Hatching for Pen-and-Ink Illustration of Surfaces, To Appear in ACM Transactions on Graphics, 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 geometric, contextual and shading features of the 3D object to these hatching 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.
Project web page
Bibtex:
@article{knbh-lhpii-12,
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 = {2012},
}
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