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A facial recognition system [1] is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image.
Eigenface. An eigenface ( / ˈaɪɡən -/ EYE-gən-) is the name given to a set of eigenvectors when used in the computer vision problem of human face recognition. [1] The approach of using eigenfaces for recognition was developed by Sirovich and Kirby and used by Matthew Turk and Alex Pentland in face classification.
Cognitive psychology. Facial perception is an individual's understanding and interpretation of the face. Here, perception implies the presence of consciousness and hence excludes automated facial recognition systems. Although facial recognition is found in other species, [1] this article focuses on facial perception in humans. The perception of ...
Esophoria is an eye condition involving inward deviation of the eye, usually due to extra-ocular muscle imbalance. It is a type of heterophoria. Cause. Causes include: Refractive errors; Divergence insufficiency; Convergence excess; this can be due to nerve, muscle, congenital or mechanical anomalies.
Incomitant strabismus cannot be fully corrected by prism glasses, because the eyes would require different degrees of prismatic correction dependent on the direction of the gaze. Incomitant strabismus of the eso- or exo-type are classified as "alphabet patterns": they are denoted as A- or V- or more rarely λ -, Y- or X-pattern depending on the ...
Automatic face detection with OpenCV. Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.
The face-space framework is a psychological model that explains how (adult) humans process and store facial information, which we use for facial recognition. It is multidimensional, with each dimension categorised by certain facial features, some of which may be: face shape, hair colour and length, distance between the eyes, age and masculinity.
3D face recognition has the potential to achieve better accuracy than its 2D counterpart by measuring geometry of rigid features on the face. This avoids such pitfalls of 2D face recognition algorithms as change in lighting, different facial expressions, make-up and head orientation.
e. 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.
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 better understanding of people’s reactions to visual stimuli.