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FaceNet is a facial recognition system developed by Florian Schroff, Dmitry Kalenichenko and James Philbina, a group of researchers affiliated with Google.The system was first presented at the 2015 IEEE Conference on Computer Vision and Pattern Recognition. [1]
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.
Eigenface provides an easy and cheap way to realize face recognition in that: Its training process is completely automatic and easy to code. Eigenface adequately reduces statistical complexity in face image representation. Once eigenfaces of a database are calculated, face recognition can be achieved in real time.
The cross race effect has a morphological basis: The facial appearance is morphologically different for different ethnic backgrounds. This has been established empirically, [35] wherein a large set of 3D scans of faces from different ethnic backgrounds was automatically clustered into groups. Only facial landmark distances were used in this ...
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 .
Bruce & Young Model of Face Recognition, 1986. One of the most widely accepted theories of face perception argues that understanding faces involves several stages: [7] from basic perceptual manipulations on the sensory information to derive details about the person (such as age, gender or attractiveness), to being able to recall meaningful details such as their name and any relevant past ...
The first step the brain does to encode a memory is to process the face. The lateral fusiform gyrus is a facial recognition area of the brain. [1] Within this brain region, the fusiform face area (FFA) analyzes the configuration and holistic appearance of the face. [4] The FFA is more activated when viewing same-race faces compared to other ...
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.