Material
Abstract
This paper presents a data-driven framework for generating cartoon-like facial representations from a given portrait image. We solve our problem by an optimization that simultaneously considers a desired artistic style, image-cartoon relationships of facial components as well as automatic adjustment of the image composition. The stylization operation consists of two steps: a face parsing step to localize and extract facial components from the input image; a cartoon generation step to cartoonize the face according to the extracted information. The components of the cartoon are assembled from a database of stylized facial components. Quantifying the similarity between facial components of input and cartoon is done by image feature matching. We incorporate prior knowledge about photo-cartoon relationships and the optimal composition of cartoon facial components extracted from a set of cartoon faces to maintain a natural and attractive look of the results.
BibTeX
@inproceedings{Zhang2014DatadrivenFace,
acmid = {2669028},
address = {New York, NY, USA},
articleno = {14},
author = {Y. Zhang and W. Dong and O. Deussen and F. Huang and K. Li and B. Hu},
booktitle = {SIGGRAPH Asia 2014 Technical Briefs},
doi = {10.1145/2669024.2669028},
isbn = {978-1-4503-2895-1},
keywords = {face alignment, face parsing, face stylization},
location = {Shenzhen, China},
numpages = {4},
pages = {14:1--14:4},
publisher = {ACM},
series = {SA '14},
title = {Data-driven Face Cartoon Stylization},
year = {2014},
url = {http://graphics.uni-konstanz.de/publikationen/Zhang2014DatadrivenFace},
}