Facial Expression Analysis Tells Us Little About Emotion | Technology Networks
The field of facial expression analysis is over a hundred years old, and has now come of age. The detection of expressions and emotions by automatic analysis has matured into a reliable methodology that is widely used in a variety of research. Ekman — essentially the father of facial expression analysis — is inevitably the prime feature of this list. It is difficult to overstate the importance of that work, as it has shaped the entirety of the facial expression analysis field.
In cognitive science and neuroscience, there have been two leading models describing how humans perceive and classify facial expressions of emotion—the continuous and the categorical model. The continuous model defines each facial expression of emotion as a feature vector in a face space. This model explains, for example, how expressions of emotion can be seen at different intensities. In contrast, the categorical model consists of C classifiers, each tuned to a specific emotion category. This model explains, among other findings, why the images in a morphing sequence between a happy and a surprise face are perceived as either happy or surprise but not something in between.