TY - JOUR
T1 - High relief from brush painting
AU - Fu, Yunfei
AU - Yu, Hongchuan
AU - Yeh, Chih Kuo
AU - Zhang, Jianjun
AU - Lee, Tong Yee
N1 - Funding Information:
We would like to thank the reviewers for many helpful comments. This work was supported in part by the Ministry of Science and Technology (106-2221-E-006-233-MY2, 107-2811-E-006-006-and 107-2221-E-006-196-MY3) and EU H2020 RISE project-AniAge (691215).
Publisher Copyright:
© 2018 IEEE.
PY - 2019/9/1
Y1 - 2019/9/1
N2 - Relief is an art form part way between 3D sculpture and 2D painting. We present a novel approach for generating a texture-mapped high-relief model from a single brush painting. Our aim is to extract the brushstrokes from a painting and generate the individual corresponding relief proxies rather than recovering the exact depth map from the painting, which is a tricky computer vision problem, requiring assumptions that are rarely satisfied. The relief proxies of brushstrokes are then combined together to form a 2.5D high-relief model. To extract brushstrokes from 2D paintings, we apply layer decomposition and stroke segmentation by imposing boundary constraints. The segmented brushstrokes preserve the style of the input painting. By inflation and a displacement map of each brushstroke, the features of brushstrokes are preserved by the resultant high-relief model of the painting. We demonstrate that our approach is able to produce convincing high-reliefs from a variety of paintings(with humans, animals, flowers, etc.). As a secondary application, we show how our brushstroke extraction algorithm could be used for image editing. As a result, our brushstroke extraction algorithm is specifically geared towards paintings with each brushstroke drawn very purposefully, such as Chinese paintings, Rosemailing paintings, etc.
AB - Relief is an art form part way between 3D sculpture and 2D painting. We present a novel approach for generating a texture-mapped high-relief model from a single brush painting. Our aim is to extract the brushstrokes from a painting and generate the individual corresponding relief proxies rather than recovering the exact depth map from the painting, which is a tricky computer vision problem, requiring assumptions that are rarely satisfied. The relief proxies of brushstrokes are then combined together to form a 2.5D high-relief model. To extract brushstrokes from 2D paintings, we apply layer decomposition and stroke segmentation by imposing boundary constraints. The segmented brushstrokes preserve the style of the input painting. By inflation and a displacement map of each brushstroke, the features of brushstrokes are preserved by the resultant high-relief model of the painting. We demonstrate that our approach is able to produce convincing high-reliefs from a variety of paintings(with humans, animals, flowers, etc.). As a secondary application, we show how our brushstroke extraction algorithm could be used for image editing. As a result, our brushstroke extraction algorithm is specifically geared towards paintings with each brushstroke drawn very purposefully, such as Chinese paintings, Rosemailing paintings, etc.
UR - https://www.scopus.com/pages/publications/85050637483
UR - https://www.scopus.com/pages/publications/85050637483#tab=citedBy
U2 - 10.1109/TVCG.2018.2860004
DO - 10.1109/TVCG.2018.2860004
M3 - Article
C2 - 30047889
AN - SCOPUS:85050637483
SN - 1077-2626
VL - 25
SP - 2763
EP - 2776
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
IS - 9
M1 - 8419282
ER -