Emotion recognition

Emotion recognition is the process of identifying human emotion, most typically from facial expressions. This is both something that humans do automatically but computational methodologies have also been developed.

Human

Humans show universal consistency in recognising emotions but also show a great deal of variability between individuals in their abilities. This has been a major topic of study in psychology.

Automatic

This process leverages techniques from multiple areas, such as signal processing, machine learning, and computer vision. The computers use different methods to interpret emotion such as Bayesian networks.^[1]

The computer programmers often use Paul Ekman's Facial Action Coding System as a guide.

Emotion recognition is used for a variety of reasons. Affectiva uses it to help advertisers and content creators to sell their products more effectively.^[2] Affectiva also makes a Q-sensor that gauges the emotions of autistic children. Emotient was an startup company which utilized artificial intelligence to predict "attitudes and actions based on facial expressions".^[3] Apple indicated its intention to buy Emotient in January 2016.^[3] nViso provides real-time emotion recognition for web and mobile applications through a real-time API.^[4] Visage Technologies AB offers emotion estimation as a part of their Visage SDK for marketing and scientific research and similar purposes.^[5] Eyeris is an emotion recognition company that works with embedded system manufacturers including car makers and social robotic companies on integrating its face analytics and emotion recognition software; as well as with video content creators to help them measure the perceived effectiveness of their short and long form video creative.^[6][7] Emotion recognition and emotion analysis are being studied by companies and universities around the world.

See also

• Face perception

References