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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 .
Emotient was a startup company which applied emotion recognition to reading frowns, smiles, and other expressions on faces, namely artificial intelligence to predict "attitudes and actions based on facial expressions". [40] Apple bought Emotient in 2016 and uses emotion recognition technology to enhance the emotional intelligence of its ...
The system is based on a robust offline face tracking stage which trains the system with different facial expressions. The matched sequences are used to build a person-specific linear face model that is subsequently used for online face tracking and expression transfer. Audio-driven techniques are particularly well fitted for speech animation.
Facial recognition systems attempt to identify a human face, which is three-dimensional and changes in appearance with lighting and facial expression, based on its two-dimensional image. To accomplish this computational task, facial recognition systems perform four steps. First face detection is used to segment the face from the image background.
The affective intent classifier was created as follows. Low-level features such as pitch mean and energy (volume) variance were extracted from samples of recorded speech. The classes of affective intent were then modeled as a gaussian mixture model and trained with these samples using the expectation-maximization algorithm .
The technique used in creating eigenfaces and using them for recognition is also used outside of face recognition: handwriting recognition, lip reading, voice recognition, sign language/hand gestures interpretation and medical imaging analysis. Therefore, some do not use the term eigenface, but prefer to use 'eigenimage'.
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.
DeepFace is a deep learning facial recognition system created by a research group at Facebook.It identifies human faces in digital images. The program employs a nine-layer neural network with over 120 million connection weights and was trained on four million images uploaded by Facebook users.