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Image Representations for Facial Expression Analysis: Comparative Study I

  • Marian Stewart Bartlett
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 612)

Abstract

Facial expressions provide an important behavioral measure for the study of emotion, cognitive processes, and social interaction. The Facial Action Coding System, (Ekman and Friesen, 1978), is an objective method for quantifying facial movement in terms of component actions. We applied computer image analysis to the problem of automatically detecting facial actions in sequences of images. In our first study we compared three approaches: Holistic spatial analysis (eigenfaces), explicit measurement of features such as wrinkles, and estimation of motion flow fields. The three methods were combined in a hybrid system which classified six upper facial actions with 91% accuracy, including low, medium, and high magnitude facial actions. The hybrid system outperformed human non-experts on this task, and performed as well as highly trained experts. These comparisons supported the theory that unsupervised feature extraction based on dependencies in the image ensemble is more effective for face image analysis than explicit measurement of facial features.

Keywords

Facial Expression Optic Flow Face Image Difference Image Facial Action 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    The term “magnitude” replaces the term “intensity” used in FACS to avoid confusion with image intensity.Google Scholar

Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Marian Stewart Bartlett
    • 1
  1. 1.Institute for Neural ComputationUniversity of CaliforniaSan DiegoUSA

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