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Automated face analysis by feature point tracking has high concurrent validity with manual FACS coding.

J F Cohn1, A J Zlochower, J Lien

  • 1University of Pittsburgh, PA, USA. jeffcohn@vms.cis.pitt.edu

Psychophysiology
|March 31, 1999
PubMed
Summary

This study introduces an automated facial display analysis system, achieving over 91% accuracy in identifying facial action units compared to manual coding. This automated method offers a rigorous and efficient approach to analyzing human behavior through facial expressions.

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Area of Science:

  • Psychology
  • Computer Science
  • Biometrics

Background:

  • Facial displays convey significant information about human behavior.
  • Current methods for coding facial displays are labor-intensive and difficult to standardize.
  • Automated analysis is needed for rigorous and efficient quantitative measurement of facial displays.

Purpose of the Study:

  • To develop and validate an automated method for facial display analysis.
  • To compare the accuracy of the automated system with manual Facial Action Coding System (FACS) coding.
  • To assess the concurrent validity of automated face analysis using feature point tracking.

Main Methods:

  • Developed an automated facial display analysis system using hierarchical optical flow estimation.
  • Tracked facial features automatically in digitized image sequences.

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  • Normalized measurements for variations in position, orientation, and scale.
  • Used discriminant function analyses on feature point measurements, with data randomly divided into training and cross-validation sets.

    • Main Results:

    • The automated system achieved high agreement with manual FACS coding in both training (≥92%) and cross-validation (91% brow, 88% eye, 81% mouth) sets.
    • Average agreement exceeded 91% for brow and eye regions in the cross-validation set.
    • Automated face analysis demonstrated high concurrent validity with manual FACS coding.

    Conclusions:

    • Automated face analysis by feature point tracking is a valid and reliable method for quantitative measurement of facial displays.
    • The developed system offers a rigorous and efficient alternative to manual FACS coding.
    • This technology has potential applications in psychology, human-computer interaction, and behavioral research.