Synthesis of exaggerative caricature with inter and intra correlations

Chien Chung Tseng, James Jenn-Jier Lien

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)


We developed a novel system consisting of two modules, statisticsbased 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.

Original languageEnglish
Title of host publicationComputer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings
Number of pages10
EditionPART 1
Publication statusPublished - 2007 Dec 1
Event8th Asian Conference on Computer Vision, ACCV 2007 - Tokyo, Japan
Duration: 2007 Nov 182007 Nov 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4843 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other8th Asian Conference on Computer Vision, ACCV 2007

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Synthesis of exaggerative caricature with inter and intra correlations'. Together they form a unique fingerprint.

Cite this