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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 .
Voluntary facial expressions are often socially conditioned and follow a cortical route in the brain. Conversely, involuntary facial expressions are believed to be innate and follow a subcortical route in the brain. Facial recognition can be an emotional experience for the brain and the amygdala is highly involved in the recognition process.
During infancy it is difficult to elicit discrete negative expressions like anger, distress and sadness, [9] and, perhaps unsurprisingly, the most common infant facial expression is the "cry-face". Cry-face is thought to integrate aspects of both anger and distress expressions and may indicate a shared basis in negative emotionality. [ 9 ]
Detail of the Mona Lisa, who is known for her smile. A smiling child. A smile is a facial expression formed primarily by flexing the muscles at the sides of the mouth.Some smiles include a contraction of the muscles at the corner of the eyes, an action known as a Duchenne smile.
Pages in category "Facial expressions" The following 36 pages are in this category, out of 36 total. This list may not reflect recent changes. ...
The muscles of the face play a prominent role in the expression of emotion, [1] and vary among different individuals, giving rise to additional diversity in expression and facial features. [29] Variations of the risorius, triangularis and zygomaticus muscles. People are also relatively good at determining if a smile is real or fake.
Microexpressions can be difficult to recognize, but still images and video can make them easier to perceive. In order to learn how to recognize the way that various emotions register across parts of the face, Ekman and Friesen recommend the study of what they call "facial blueprint photographs", photographic studies of "the same person showing all the emotions" under consistent photographic ...
According to the study, while most of facial images' predictive power is attributable to basic demographics (age, gender, race) extracted from the face, image artifacts, observable facial characteristics, and other image features extracted by deep learning all contribute to prediction quality beyond demographics.