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A facial recognition system 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.
An anti-facial recognition mask is a mask which can be worn to confuse facial recognition software. This type of mask is designed to thwart the surveillance of people by confusing the biometric data. There are many different types of masks which are used to trick facial recognition technology.
Biometric technology hit the shelves in late 2011 with the release of Android's then-latest operating system, which let users unlock their screens using facial recognition.
Prism dioptres. Prism correction is commonly specified in prism dioptres, a unit of angular measurement that is loosely related to the dioptre. Prism dioptres are represented by the Greek symbol delta (Δ) in superscript. A prism of power 1 Δ would produce 1 unit of displacement for an object held 100 units from the prism. [2]
The Face Recognition Vendor Test (FRVT) was a series of large scale independent evaluations for face recognition systems realized by the National Institute of Standards and Technology in 2000, 2002, 2006, 2010, 2013 and 2017.
The fusiform face area (FFA, meaning spindle-shaped face area) is a part of the human visual system (while also activated in people blind from birth) that is specialized for facial recognition. It is located in the inferior temporal cortex (IT) , in the fusiform gyrus ( Brodmann area 37 ).
Three-dimensional face recognition ( 3D face recognition) is a modality of facial recognition methods in which the three-dimensional geometry of the human face is used. It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts, rivaling fingerprint recognition .
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.
Facial recognition or face recognition may refer to: Face detection, often a step done before facial recognition; Face perception, the process by which the human brain understands and interprets the face; Pareidolia, which involves, in part, seeing images of faces in clouds and other scenes
There are three main areas for improving face recognition algorithms: high-resolution images, three-dimensional (3D) face recognition, and new pre-processing techniques. Current face recognition systems are designed to work with relatively small, static facial images.