Emotion classification can be more formally written as the measure of affect in someone.
The purpose of learning about emotion classification is to implement some of the ideas proposed in emotion ai
Research in the emotion classification field is quite polarizing. The two main viewpoints are:
- that emotions are discrete and fundamentally different constructs, called the Discrete Emotion Theory
- that emotions can be characterized on a dimensional basis in groupings. There are multiple Dimensional models of emotion
For most purposes we will use the Circumplex Model of Emotion, however for more info, see A Comparison of Dimensional Models of Emotion
In a technical sense, there are a couple main heuristics to classify emotions:
- Facial expression
- Speech
- Posture
- Gestures
- Choice of articulation
- Physiological signals
- EEG
- EOG
- ECG
- EMG
- GSR
- Eye tracking
