ACM Transactions on Graphics· 2012Q1
Learning hatching for pen-and-ink illustration of surfaces
- 649citations
- Q1SCImago
- 2012year
Short summary
A new algorithm learns to automatically generate pen-and-ink hatching illustrations in a specific artist's style by analyzing a single example drawing.
AI-generated from the title and abstract; the full text is not read.
Key points
- Algorithm analyzes per-pixel hatching properties (level, orientation, spacing, intensity, length, thickness) from an artist's drawing.
- Learns a mapping from 3D object features (geometric, contextual, shading) to hatching properties.
- Enables automatic generation of new illustrations in the artist's learned style for novel views.
- Uses classification, regression, and clustering techniques for style learning.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. ACM Transactions on Graphics, 2012 · DOI ↗
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Field: Computer Graphics and Computer-Aided Design
Computer Graphics and Computer-Aided DesignComputer Science