Greedy Image Approximation for Artwork Generation via Contiguous Bézier Segments
No Thumbnail Available
Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
The automatic creation of digital art has a long history in computer graphics. In this work, we focus on approximating input images to mimic artwork by the artist Kumi Yamashita, as well as the popular scribble art style. Both have in common that the artists create the works by using a single, contiguous thread (Yamashita) or stroke (scribble) that is placed seemingly at random when viewed at close range, but perceived as a tone-mapped picture when viewed from a distance. Our approach takes a rasterized image as input and creates a single, connected path by iteratively sampling a set of candidate segments that extend the current path and greedily selecting the best one. The candidates are sampled according to art style specific constraints, i.e. conforming to continuity constraints in the mathematical sense for the scribble art style. To model the perceptual discrepancy between close and far viewing distances, we minimize the difference between the input image and the image created by rasterizing our path after applying the contrast sensitivity function, which models how human vision blurs images when viewed from a distance. Our approach generalizes to colored images by using one path per color. We evaluate our approach on a wide range of input images and show that it is able to achieve good results for both art styles in grayscale and color.
Description
CCS Concepts: Computing methodologies → Non-photorealistic rendering; Applied computing → Media arts
@inproceedings{10.2312:vmv.20231234,
booktitle = {Vision, Modeling, and Visualization},
editor = {Guthe, Michael and Grosch, Thorsten},
title = {{Greedy Image Approximation for Artwork Generation via Contiguous Bézier Segments}},
author = {Nehring-Wirxel, Julius and Lim, Isaak and Kobbelt, Leif},
year = {2023},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-232-5},
DOI = {10.2312/vmv.20231234}
}