Visual Computing

University of Konstanz
SIGGRAPH Asia 2014 Technical Briefs

Data-driven Face Cartoon Stylization

Y. Zhang, W. Dong, O. Deussen, F. Huang, K. Li, B. Hu

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},
}

Supplemental Material

Paper (.pdf, 15.7 MB)