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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 .
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 ...
Three-dimensional face recognition algorithms identify faces based on the 3D shape of a person’s face. Unlike current face recognition systems that are affected by changes in lighting and pose, 3D face recognition has the potential to improve performance under these conditions, as the shape of faces remains unaffected.
Facial motion capture is the process of electronically converting the movements of a person's face into a digital database using cameras or laser scanners. This database may then be used to produce computer graphics (CG), computer animation for movies, games, or real-time avatars. Because the motion of CG characters is derived from the ...
Motion capture of two pianists ' right hands playing the same piece (slow-motion, no-sounds) [1] Two repetitions of a walking sequence recorded using motion capture [2] Motion capture (sometimes referred as mo-cap or mocap, for short) is the process of recording the movement of objects or people. It is used in military, entertainment, sports ...
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