Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting
Abstract
Oriental ink painting, called Sumi-e, is one of the most appealing painting styles that has attracted artists around the world. Major challenges in computer-based Sumi-e simulation are to abstract complex scene information and draw smooth and natural brush strokes. To automatically generate such strokes, we propose to model a brush as a reinforcement learning agent, and learn desired brush-trajectories by maximizing the sum of rewards in the policy search framework. We also elaborate on the design of actions, states, and rewards tailored for a Sumi-e agent. The effectiveness of our proposed approach is demonstrated through simulated Sumi-e experiments.
Cite
Text
Xie et al. "Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting." International Conference on Machine Learning, 2012. doi:10.1587/transinf.E96.D.1134Markdown
[Xie et al. "Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting." International Conference on Machine Learning, 2012.](https://mlanthology.org/icml/2012/xie2012icml-artist/) doi:10.1587/transinf.E96.D.1134BibTeX
@inproceedings{xie2012icml-artist,
title = {{Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting}},
author = {Xie, Ning and Hachiya, Hirotaka and Sugiyama, Masashi},
booktitle = {International Conference on Machine Learning},
year = {2012},
doi = {10.1587/transinf.E96.D.1134},
url = {https://mlanthology.org/icml/2012/xie2012icml-artist/}
}