Semi-supervised Learning of Caricature Pattern from Manifold Regularization

  • Junfa Liu
  • Yiqiang Chen
  • Jinjing Xie
  • Xingyu Gao
  • Wen Gao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5371)


Automatic caricature synthesis is to transform the input face to an exaggerated one. It is becoming an interesting research topic, but it remains an open issue to specify the caricature’s pattern for the input face. This paper proposed a novel pattern prediction method based on MR (manifold regularization), which comprises three steps. Firstly, we learn the caricature pattern by manifold dimension reduction, and select some low dimensional caricature pattern as the labels for corresponsive true faces. Secondly, manifold regularization is performed to build a semi-supervised regression between true faces and the pattern labels. In the third step of offline phase, the input face is mapped to a pattern label by the learnt regressive model, and the pattern label is further transformed to caricature parameters by a locally linear reconstruction algorithm. This approach takes advantage of manifold structure lying in both true faces and caricatures. Experiments show that, low dimensional manifold represents the caricature pattern well and the semi-supervised regressive model from manifold regularization can predict the target caricature pattern successfully.


Pattern Label Unlabeled Sample Mesh Parameter Input Face Facial Mesh 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Junfa Liu
    • 1
    • 2
  • Yiqiang Chen
    • 1
  • Jinjing Xie
    • 1
    • 2
  • Xingyu Gao
    • 1
  • Wen Gao
    • 1
    • 3
  1. 1.Institute of Computing TechnologyChinese Academy of SciencesBeijingChina
  2. 2.Graduate School of Chinese Academy of SciencesBeijingChina
  3. 3.Institute of Digital MediaPeking UniversityBeijingChina

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