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The computer synthesis of expressive faces.

K Waters1, D Terzopoulos

  • 1Digital Equipment Corporation, Cambridge Research Lab, Massachusetts 02139.

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|January 29, 1992
PubMed
Summary
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This study introduces a novel method for creating realistic computer-generated faces with expressive movements. It uses a 3D facial model with physics-based tissue and muscle simulations for enhanced facial animation.

Area of Science:

  • Computer graphics
  • Computer vision
  • Biomedical engineering

Background:

  • Realistic facial animation is crucial for virtual characters in various applications.
  • Existing methods often struggle to capture the complex interplay between facial muscles and tissue dynamics.
  • A need exists for a robust methodology that integrates anatomical and physical principles for facial synthesis.

Purpose of the Study:

  • To develop a novel methodology for the computer synthesis of realistic and expressive human faces.
  • To create a sophisticated 3D facial model incorporating both physical tissue properties and anatomical muscle structures.
  • To enable automatic mapping of generic models onto specific facial geometries for personalized synthesis.

Main Methods:

  • Developed a generic 3D facial model with integrated physical tissue and anatomical muscle components.

Related Experiment Videos

  • Utilized photogrammetry and range sensors to acquire detailed facial geometries.
  • Implemented automatic mapping of generic models onto specific facial representations.
  • Employed a performance-driven animation technique to estimate facial muscle dynamics from video imagery.

    • Main Results:

    • Achieved superior realism in synthesized faces through physics-based simulation of tissue deformation.
    • Demonstrated the ability to create expressive articulations by emulating coordinated facial muscle activity.
    • Successfully mapped generic models onto diverse facial geometries, enabling personalized face synthesis.

    Conclusions:

    • The proposed methodology provides a significant advancement in realistic facial synthesis and animation.
    • The integration of physical modeling and anatomical muscle simulation leads to highly expressive and lifelike digital faces.
    • This approach has broad implications for fields requiring realistic human character representation, such as in gaming, film, and virtual reality.