Facial Expression Analysis

  • Fernando De la Torre
  • Jeffrey F. Cohn


The face is one of the most powerful channels of nonverbal communication. Facial expression provides cues about emotion, intention, alertness, pain, personality, regulates interpersonal behavior, and communicates psychiatric and biomedical status among other functions. Within the past 15 years, there has been increasing interest in automated facial expression analysis within the computer vision and machine learning communities. This chapter reviews fundamental approaches to facial measurement by behavioral scientists and current efforts in automated facial expression recognition. We consider challenges, review databases available to the research community, approaches to feature detection, tracking, and representation, and both supervised and unsupervised learning.


Facial Expression Facial Expression Recognition Facial Action Active Appearance Model Facial Animation 
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.



This work was partially supported by National Institute of Health Grant R01 MH 051435, and the National Science Foundation under Grant No. EEC-0540865. Thanks to Tomas Simon, Minh H. Nguyen, Feng Zhou, Simon Baker, Simon Lucey and Iain Matthews for helpful discussions, and some figures.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Robotics InstituteCarnegie Mellon UniversityPittsburghUSA
  2. 2.Department of PsychologyUniversity of PittsburghPittsburghUSA

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