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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. To date, the most work has been conducted on automating the recognition of facial expressions from video, spoken expressions from audio, written expressions from text ...
Researchers work with three types of databases, such as a database of peak expression images only, a database of image sequences portraying an emotion from neutral to its peak, and video clips with emotional annotations. Many facial expression databases have been created and made public for expression recognition purpose.
Facial coding is the process of measuring human emotions through facial expressions. Emotions can be detected by computer algorithms for automatic emotion recognition that record facial expressions via webcam. This can be applied to a better understanding of people’s reactions to visual stimuli.
A facial expression database is a collection of images or video clips with facial expressions of a range of emotions. Well-annotated ( emotion -tagged) media content of facial behavior is essential for training, testing, and validation of algorithms for the development of expression recognition systems .
In relation to computers and body language, research is being done with the use of mathematics in order to teach computers to interpret human movements, hand gestures and even facial expressions. This is different from the normal way people generally communicate with computers for example with the click of the mouse, keyboard, or any physical ...
Kismet is a robot head which was made in the 1990s at Massachusetts Institute of Technology by Dr. Cynthia Breazeal as an experiment in affective computing; a machine that can recognize and simulate emotions. The name Kismet comes from a Turkish word meaning "fate" or sometimes "luck". [1]
Gesture recognition is an area of research and development in computer science and language technology concerned with the recognition and interpretation of human gestures. A subdiscipline of computer vision , [ citation needed ] it employs mathematical algorithms to interpret gestures.
The development of FACS tools for different species allows the objective and anatomical study of facial expressions in communicative and emotional contexts. Furthermore, a cross-species analysis of facial expressions can help to answer interesting questions, such as which emotions are uniquely human. [21]