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Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context.
The face expresses a great deal of emotion, however, there are two main facial muscle groups that are usually studied to detect emotion: The corrugator supercilii muscle, also known as the 'frowning' muscle, draws the brow down into a frown, and therefore is the best test for negative, unpleasant emotional response.↵The zygomaticus major ...
The emotion annotation can be done in discrete emotion labels or on a continuous scale. Most of the databases are usually based on the basic emotions theory (by Paul Ekman) which assumes the existence of six discrete basic emotions (anger, fear, disgust, surprise, joy, sadness). However, some databases include the emotion tagging in continuous ...
Face detection can be used as part of a software implementation of emotional inference. Emotional inference can be used to help people with autism understand the feelings of people around them. [8] AI-assisted emotion detection in faces has gained significant traction in recent years, employing various models to interpret human emotional states.
Real-time face detection in video footage became possible in 2001 with the Viola–Jones object detection framework for faces. [28] Paul Viola and Michael Jones combined their face detection method with the Haar-like feature approach to object recognition in digital images to launch AdaBoost, the first real-time frontal-view face detector. [29]
The response format that is most commonly used in emotion recognition studies is forced choice. In forced choice, for each facial expression, participants are asked to select their response from a short list of emotion labels. The forced choice method determines the emotion attributed to the facial expressions via the labels that are presented ...
Emotion classification, the means by which one may distinguish or contrast one emotion from another, is a contested issue in emotion research and in affective science. Researchers have approached the classification of emotions from one of two fundamental viewpoints: [citation needed] that emotions are discrete and fundamentally different constructs
The facial feedback hypothesis, rooted in the conjectures of Charles Darwin and William James, is that one's facial expression directly affects their emotional experience. . Specifically, physiological activation of the facial regions associated with certain emotions holds a direct effect on the elicitation of such emotional states, and the lack of or inhibition of facial activation will ...