We introduce a novel approach to modeling the dynamics of human facial motion induced by the action of speech for the purpose of synthesis. We represent the trajectories of a number of salient features on the human face as the output of a dynamical system made up of two subsystems, one driven by the deterministic speech input, and a second driven by an unknown stochastic input. Inference of the model (learning) is performed automatically and involves an extension of independent component analysis to time-depentend data. Using a shapetexture decompositional representation for the face, we generate facial image sequences reconstructed from synthesized feature point positions.

Modeling and synthesis of facial motion driven by speech

CHIUSO, ALESSANDRO;
2004

Abstract

We introduce a novel approach to modeling the dynamics of human facial motion induced by the action of speech for the purpose of synthesis. We represent the trajectories of a number of salient features on the human face as the output of a dynamical system made up of two subsystems, one driven by the deterministic speech input, and a second driven by an unknown stochastic input. Inference of the model (learning) is performed automatically and involves an extension of independent component analysis to time-depentend data. Using a shapetexture decompositional representation for the face, we generate facial image sequences reconstructed from synthesized feature point positions.
Computer Vision - ECCV 2004
9783540219811
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/1337747
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