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Synthesis of Exaggerative Caricature with Inter and Intra Correlations

  • Chien-Chung Tseng
  • Jenn-Jier James Lien
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4843)

Abstract

We developed a novel system consisting of two modules, statistics-based synthesis and non-photorealistic rendering (NPR), to synthesize caricatures of exaggerated facial features and other particular characteristics, such as beards or nevus. The statistics-based synthesis module can exaggerate shapes and positions of facial features based on non-linear exaggerative rates determined automatically. Instead of comparing only the inter relationship between features of different subjects at the existing methods, our synthesis module applies both inter and intra (i.e. comparisons between facial features of the same subject) relationships to make the synthesized exaggerative shape more contrastive. Subsequently, the NPR module generates a line-drawing sketch of original face, and then the sketch is warped to an exaggerative style with synthesized shape points. The experimental results demonstrate that this system can automatically, and effectively, exaggerate facial features, thereby generating corresponding facial caricatures.

Keywords

Exaggerative rate Exaggerative caricature synthesis Eigenspace Non-photorealistic rendering (NPR) 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Chien-Chung Tseng
    • 1
  • Jenn-Jier James Lien
    • 1
  1. 1.Robotics Laboratory, Dept. of Computer Science and Information Engineering, National Cheng Kung University, No. 1, Ta-Hsueh Road, TainanTaiwan

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