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Face Recognition is used to identify or verify a person from a digital image or a video source using a pre-stored facial data. Visage SDK's face recognition algorithms can measure similarities between people and recognize a person’s identity [citation needed] from a frontal facial image by comparing it to pre-stored faces.
A facial motion capture database describes the coordinates or relative positions of reference points on the actor's face. The capture may be in two dimensions, in which case the capture process is sometimes called "expression tracking", or in three dimensions. Two-dimensional capture can be achieved using a single camera and capture software.
The following tables compare general and technical information for a number of streaming media systems both audio and video. Please see the individual systems' linked articles for further information.
The system is based on a robust offline face tracking stage which trains the system with different facial expressions. The matched sequences are used to build a person-specific linear face model that is subsequently used for online face tracking and expression transfer. Audio-driven techniques are particularly well fitted for speech animation.
Faceware Live aims to create natural looking faces and facial expressions in real-time. Any video source can be used with the software's one-button calibration. The captured video is transferred onto a 3D animated character. This process combines image processing and data streaming to translate facial expressions into a set of animation values ...
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Facial recognition software at a US airport Automatic ticket gate with face recognition system in Osaka Metro Morinomiya Station. 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.