Synthesizing style-preserving cartoons via non-negative style factorization

Zhang LIANG; Jun XIAO; Yue-ting ZHUANG

doi:10.1631/jzus.C1100202

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Synthesizing style-preserving cartoons via non-negative style factorization

Computer & Automation | Updated：2022-12-09

- Synthesizing style-preserving cartoons via non-negative style factorization
- Synthesizing style-preserving cartoons via non-negative style factorization
- Frontiers of Information Technology & Electronic Engineering Vol. 13, Issue 3, Pages: 196-207(2012)
- Affiliations：
  
  Institute of Artificial Intelligence, School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
- Author bio：
  
  [ "Zhang LIANG, E-mail: liangzhang@zju.edu.cn" ]
  Jun XIAO, E-mail: junx@zju.edu.cn
  [ "Yue-ting ZHUANG, E-mail: yzhuang@zju.edu.cn" ]
- Funds：
- DOI：10.1631/jzus.C1100202
  CLC： TP391
- Received：08 July 2011，
  
  Revised：2012-;2-;8，
  
  Published：2012-03
- Accepted：
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Zhang LIANG, Jun XIAO, Yue-ting ZHUANG. Synthesizing style-preserving cartoons via non-negative style factorization[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(3): 196-207.
DOI：

Zhang LIANG, Jun XIAO, Yue-ting ZHUANG. Synthesizing style-preserving cartoons via non-negative style factorization[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(3): 196-207. DOI： 10.1631/jzus.C1100202.

摘要

Abstract

We present a complete framework for synthesizing style-preserving 2D cartoons by learning from traditional Chinese cartoons. In contrast to reusing-based approaches which rely on rearranging or retrieving existing cartoon sequences

we aim to generate stylized cartoons with the idea of style factorization. Specifically

starting with 2D skeleton features of cartoon characters extracted by an improved rotoscoping system

we present a non-negative style factorization (NNSF) algorithm to obtain style basis and weights and simultaneously preserve class separability. Thus

factorized style basis can be combined with heterogeneous weights to re-synthesize style-preserving features

and then these features are used as the driving source in the character reshaping process via our proposed subkey-driving strategy. Extensive experiments and examples demonstrate the effectiveness of the proposed framework.

关键词

Keywords

references

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