Automatic Extraction of Facial Action Codes
Two systems for capturing and analyzing automatically facial expressions are evaluated and compared. The systems, developed by interdisciplinary research teams at CMU/Pitt and UCSD/Salk, are the first attempt at automatically analyzing spontaneous facial expressions with unconstrained head orientation. The training and test sequences where acquired by Ekman and Frank while the subject was engaged in deception in a realistic scenario. Facial analysis is based on the extraction of action units as defined by Ekman in his classic Facial Action Coding System. While full automation has not yet been achieved the systems correctly classified around 90% of instances of 3 facial movements, or Action Units. The objective of a fully automated system for measuring human expression from facial and body motion and, possibly, speech cues, is a realistic goal for the next 10 years. Applications in intelligence and security, human-machine interfaces, and psychology will be enabled by this technology. The next step to be taken in order to achieve this goal is the acquisition of a 10x larger and better (more sensors and higher resolution) dataset. This should be followed by the creation of a community of interdisciplinary teams working towards this goal.