Ekman s facial action coding system

Friesen, and published in Hager published a significant update to FACS in Due to subjectivity and time consumption issues, FACS has been established as a computed automated system that detects faces in videos, extracts the geometrical features of the faces, and then produces temporal profiles of each facial movement. Using FACS [5] human coders can manually code nearly any anatomically possible facial expression, deconstructing it into the specific action units AU and their temporal segments that produced the expression. As AUs are independent of any interpretation, they can be used for any higher order decision making process including recognition of basic emotions , or pre-programmed commands for an ambient intelligent environment. It also defines a number of Action Descriptors, which differ from AUs in that the authors of FACS have not specified the muscular basis for the action and have not distinguished specific behaviors as precisely as they have for the AUs.

Many researchers code muscle movements to learn more about how and why the face moves. They use the Facial Action Coding System which provides them with a technique for the reliable coding and analysis of facial movements and expressions. They indicate which AUs moved to produce the changes observed in the face. This makes FACS coding quite objective. In scoring, it will be necessary to apply slow motion and frame-by-frame viewing to identify the AUs that occur, always alternating with real time viewing.

It is the most popular standard currently used to systematically categorize the physical expression of emotions, and it has proven useful both to psychologists and to animators. While using the system for several years in their lab and training new FACS coders, they updated the rules and definitions of the system. At first the changes were handed out to the new FACS coders in form of an addendum. However, as changes became more structural, a new version of FACS was needed.

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