Continuous Curve Textures

ACM Transactions on Graphics (Proc. SIGGRAPH Asia), 2020


Given a small input exemplar (left), our method synthesizes a larger output result (right).
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Abstract

Repetitive patterns are ubiquitous in natural and man-made objects, with a variety of development tools and methods. Manual authoring provides unprecedented degree of freedom and control, but can require significant artistic expertise and manual labor. Computational methods can automate parts of the manual creation process, but are mainly tailored for discrete pixels or elements instead of more general continuous structures. We propose an example-based method to synthesize continuous curve patterns from exemplars. Our main idea is to extend prior sample-based discrete element synthesis methods to consider not only sample positions (geometry) but also their connections (topology). Since continuous structures can exhibit higher complexity than discrete elements, we also propose robust, hierarchical synthesis to enhance output quality. Our algorithm can generate a variety of continuous curve patterns fully automatically. For further quality improvement and customization, we also present an autocomplete user interface to facilitate interactive creation and iterative editing. We evaluate our methods and interface via different patterns, ablation studies, and comparisons with alternative methods.

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Citation

@article{Tu:2020:CCT,
 title = {Continuous Curve Textures},
 author = {Peihan Tu and Li-Yi Wei and Koji Yatani and Takeo Igarashi and Matthias Zwicker},
 journal = {ACM Trans. Graph.},
 volume = {39},
 number = {6},
 articleno = {168},
 doi = {10.1145/3414685.3417780},
 year = 2020,
 month = 12,
}

Contact

For questions and clarifications, please get in touch with:
Peihan Tu phtu@cs.umd.edu

Template from GVV Group at MPI.