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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.
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. [1][2] The Facebook Research team has stated that ...
Face detection. 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. [1] Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. [2]
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 [1]) that is specialized for facial recognition. [2] It is located in the inferior temporal cortex (IT), in the fusiform gyrus (Brodmann area 37).
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 facial features is ...
Informally, eigenfaces can be considered a set of "standardized face ingredients", derived from statistical analysis of many pictures of faces. Any human face can be considered to be a combination of these standard faces. For example, one's face might be composed of the average face plus 10% from eigenface 1, 55% from eigenface 2, and even −3 ...
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