Emotions Prediction
Let’s learn to extract emotions from a face image.
Introduction
For decades, decoding the emotional expressions of a face has been an interesting topic for research in the field of psychology and, more recently, in the field of human-computer interaction (HCI) because of its significant commercial potential.
Facial expressions are an intuitive reflection of a person’s mental state and a common form of non-verbal communication. Most people can effectively express their personal feelings and communicate their intentions through facial expressions.
What is Facial Emotion Recognition (FER)?
Facial Emotional Recognition (FER) is mainly a technology designed to analyze the sentiments captured by different forms of media, such as pictures and videos. Built on top of AI, FER belongs to the affective computing family of technologies. It detects and analyzes different facial expressions in order to conclude what emotions a person is showing.
The table below depicts the top emotions along with their respective and most common facial expressions:
Most common expressions
Emotion | Related Facial Expressions |
Happy | Corners of mouth raised into a smile |
Sad | Furrowed brows, lip corner depressor |
Fear | Open mouth, wide eyes, furrowed brows |
Anger | Intense gaze, lowered eyebrows, raised chin |
Surprise | Dropped jaw, raised brows, wide eyes |
Disgust | Eyebrows pulled down, nose wrinkled, upper lip pulled up, loose lips |
Neutral | Neutral postures of the face |
What are the applications of FER?
FER usage may cover an extensive variety of applications, including the following:
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Analyzing customer behavior for ...