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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.

Contents

HumanEdit

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.

AutomaticEdit

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 a 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] ParallelDots have a emotion detction API to detect emotion from visual and textual data which uses convolutional neural networks for implementing emotion classification as it is a feature detection type of task.[4] nViso provides real-time emotion recognition for web and mobile applications through a real-time API.[5] Visage Technologies AB offers emotion estimation as a part of their Visage SDK for marketing and scientific research and similar purposes.[6] 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.[7][8] Emotion recognition and emotion analysis are being studied by companies and universities around the world.

See alsoEdit

ReferencesEdit

  1. ^ Miyakoshi, Yoshihiro, and Shohei Kato. "Facial Emotion Detection Considering Partial Occlusion Of Face Using Baysian Network". Computers and Informatics (2011): 96–101.
  2. ^ "Affectiva". 
  3. ^ a b DeMuth Jr., Chris (8 January 2016). "Apple Reads Your Mind". M&A Daily. Seeking Alpha. Retrieved 9 January 2016. 
  4. ^ Gargi Sharma (April 21, 2017). "Emotion Detection Using Machine Learning". ParallelDots. 
  5. ^ "nViso". nViso.ch. 
  6. ^ "Visage Technologies". 
  7. ^ "Feeling sad, angry? Your future car will know". 
  8. ^ "Cars May Soon Warn Drivers Before They Nod Off".