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3D model of a human face. 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.
The generation of new faces is based on a pre-existing database of example faces acquired through a 3D scanning procedure. All these faces are in dense point-to-point correspondence, which enables the generation of a new realistic face (morph) by combining the acquired faces. A new 3D face can be inferred from one or multiple existing images of ...
FaceGen 3.3 allows the user to randomize, tween, normalize and exaggerate faces, and also includes algorithms for adjusting apparent age, ethnicity and gender. It also allows limited parametric control of facial expressions, and includes a set of phoneme expressions for the animation of characters with "speaking" roles.
Mixamo also provides an online, automatic model rigging service known as the Auto-Rigger, which was the industry's first online rigging service. The AutoRigger applies machine learning to understand where the limbs of a 3D model are and to insert a "skeleton", or rig, into the 3D model as well as calculating the skinning weights.
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.
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