BibTex
@inproceedings{Olivier:2022:10.20380/GI2022.17,
author = {Olivier, Pauline and Memari, Pooran and Cani, Marie-Paule},
title = {Structured Shape-Patterns from a Sketch: A Multi-Scale Approach},
booktitle = {Proceedings of Graphics Interface 2022},
series = {GI 2022},
year = {2022},
issn = {0713-5424},
location = {Montr{\'e}al, Quebec},
pages = {161 -- 170},
numpages = {9},
doi = {10.20380/GI2022.17},
publisher = {Canadian Information Processing Society},
}
Abstract
Structured 2D patterns formed by the anisotropic distribution of arbitrary shapes are ubiquitous in nature and man-made environments. They may include both bounded and unbounded (extended fiber-like) shapes. In this work, we address the problem of interactively generating such patterns from a single exemplar sketched by a user. We build our solution on a new data structure, the Support Structure Hierarchy, computed from a multi-resolution analysis of the input exemplar, that encodes the main anisotropy directions at different scales as well as deviations from them. We propose an efficient method based on this structure to synthesize a similar distribution of shapes in an extended 2D domain. The user can also choose to hybridize multiple input exemplars by combining structural shapes extracted at different scales. As shown in a user study, our multi-scale solution generates structured shape-patterns that perceptually compete with state-of-the-art methods, whether learning-based or not. Moreover, our interactive solution, which requires no pre-calculation, fits well with the needs of an interactive authoring tool, where the user can not only sketch and extend 2D vector textures but also combine them seamlessly.