Permanent link to this recordhttp://hdl.handle.net/10754/598714
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AbstractThis 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. © 2012 ACM.
CitationKalogerakis E, Nowrouzezahrai D, Breslav S, Hertzmann A (2012) Learning hatching for pen-and-ink illustration of surfaces. ACM Transactions on Graphics 31: 1–17. Available: http://dx.doi.org/10.1145/2077341.2077342.
SponsorsThis project was funded by NSERC, CIFAR, CFI, the Ontario MRI, and KAUST Global Collaborative Research.
JournalACM Transactions on Graphics