Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/140472
Title: Globally consistent wrinkle-aware shading of line drawings
Authors: Jayaraman, Pradeep Kumar
Fu, Chi-Wing
Zheng, Jianmin
Liu, Xueting
Wong, Tien-Tsin
Keywords: Engineering::Computer science and engineering
Issue Date: 2017
Source: Jayaraman, P. K., Fu, C.-W., Zheng, J., Liu, X., & Wong, T.-T. (2018). Globally consistent wrinkle-aware shading of line drawings. IEEE Transactions on Visualization and Computer Graphics, 24(7), 2103-2117. doi:10.1109/TVCG.2017.2705182
Journal: IEEE Transactions on Visualization and Computer Graphics 
Abstract: Shading is a tedious process for artists involved in 2D cartoon and manga production given the volume of contents that the artists have to prepare regularly over tight schedule. While we can automate shading production with the presence of geometry, it is impractical for artists to model the geometry for every single drawing. In this work, we aim to automate shading generation by analyzing the local shapes, connections, and spatial arrangement of wrinkle strokes in a clean line drawing. By this, artists can focus more on the design rather than the tedious manual editing work, and experiment with different shading effects under different conditions. To achieve this, we have made three key technical contributions. First, we model five perceptual cues by exploring relevant psychological principles to estimate the local depth profile around strokes. Second, we formulate stroke interpretation as a global optimization model that simultaneously balances different interpretations suggested by the perceptual cues and minimizes the interpretation discrepancy. Lastly, we develop a wrinkle-aware inflation method to generate a height field for the surface to support the shading region computation. In particular, we enable the generation of two commonly-used shading styles: 3D-like soft shading and manga-style flat shading.
URI: https://hdl.handle.net/10356/140472
ISSN: 1941-0506
DOI: 10.1109/TVCG.2017.2705182
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TVCG.2017.2705182
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:IMI Journal Articles

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