A feature-preserved simplification for autonomous facial animation from 3D scan data

Soo Kyun Kim, Sun Jeong Kim, Chang Hun Kim

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We propose a new simplification algorithm of facial models for animation. For the facial animation, the models are often simplified from complex scan data based on geometric features, but it leads to decrease the quality and such features are easily noticed by human perception. For example, a lip line and eyebrows easily lose their details by geometry-based simplification. In this paper, facial features are extracted using an image processing of a 2D texture image and the curvature analysis of the 3D geometry, which improves the details around the feature areas of the facial model. Especially if lip contact line is simplified to one or two edges, it may not be proper for lip animation. Finally, we will show that our simplified model can produce as good as a facial animation as the one from the original model.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsVipin Kumar, Marina L. Gavrilova, Chih Jeng Kenneth Tan, Pierre L’Ecuyer, Chih Jeng Kenneth Tan
PublisherSpringer Verlag
Pages640-649
Number of pages10
ISBN (Print)3540401563
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2669
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kim, S. K., Kim, S. J., & Kim, C. H. (2003). A feature-preserved simplification for autonomous facial animation from 3D scan data. In V. Kumar, M. L. Gavrilova, C. J. Kenneth Tan, P. L’Ecuyer, & C. J. Kenneth Tan (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 640-649). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2669). Springer Verlag. https://doi.org/10.1007/3-540-44842-x_65