  A look is worth a thousand words is a popular phrase. And why is a simple
look enough to portray our feelings about something or someone? Behind this
question are the theoretical foundations of the field of psychology regarding
social cognition and the studies of psychologist Paul Ekman. Facial
expressions, as a form of non-verbal communication, are the primary way to
transmit emotions between human beings. The set of movements and expressions of
facial muscles that convey some emotional state of the individual to their
observers are targets of studies in many areas. Our research aims to evaluate
Ekman's action units in datasets of real human faces, posed and spontaneous,
and virtual human faces resulting from transferring real faces into Computer
Graphics faces. In addition, we also conducted a case study with specific movie
characters, such as SheHulk and Genius. We intend to find differences and
similarities in facial expressions between real and CG datasets, posed and
spontaneous faces, and also to consider the actors' genders in the videos. This
investigation can help several areas of knowledge, whether using real or
virtual human beings, in education, health, entertainment, games, security, and
even legal matters. Our results indicate that AU intensities are greater for
posed than spontaneous datasets, regardless of gender. Furthermore, there is a
smoothing of intensity up to 80 percent for AU6 and 45 percent for AU12 when a
real face is transformed into CG.
