Learning hatching for pen-and-ink illustration of surfaces

TLDR

An artist typically creates a single hatching illustration of a 3D object. The article introduces an algorithm that learns an artist’s hatching style from line drawings. The authors analyze strokes to extract per‑pixel hatching attributes, learn a mapping from 3D geometric and shading features to these attributes using classification, regression, and clustering, and then synthesize new illustrations by applying the mapping to generate strokes in the artist’s style.

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.