“Learning Hatching for Pen-and-Ink Illustration of Surfaces” by Kalogerakis, Nowrouzezahrai, Breslav and Hertzmann

  • ©Evangelos Kalogerakis, Derek Nowrouzezahrai, Simon Breslav, and Aaron Hertzmann

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Title:

    Learning Hatching for Pen-and-Ink Illustration of Surfaces

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Abstract:


    This article presents an algorithm for learning hatching styles from line drawings. An artist draws a single hatching illustration of a 3D object. Her 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.

References:


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