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Title A Comprehensive System for Facial Animation of Generic 3D Head Models Driven by Speech
Authors Lucas D. Terissi, Mauricio Cerda, Juan C. Gomez, Nancy Hitschfeld, Bernard Girau
Publication date February 2013
Abstract A comprehensive system for facial animation of generic 3D
head
models driven by speech is presented in this article. In the training stage,
audio-visual information is extracted from audio-visual training data, and
then used to compute the parameters of a single joint audio-visual hidden
Markov model (AV-HMM). In contrast to most of the methods in the literature,
the proposed approach does not require segmentation/classification
processing stages of the audio-visual data, avoiding the error propagation
related to these procedures. The trained AV-HMM provides a compact
representation of the audio-visual data, without the need of phoneme (word)
segmentation, which makes it adaptable to different languages. Visual
features are estimated from the speech signal based on the inversion of the
AV-HMM. The estimated visual speech features are used to animate a simple
face model. The animation of a more complex head model is then obtained by
automatically mapping the deformation of the simple model to it, using a
small number of control points for the interpolation. The proposed algorithm
allows the animation of 3D head models of arbitrary complexity through a
simple setup procedure. The resulting animation is evaluated in terms of
intelligibility of visual speech through perceptual tests, showing a
promising performance. The computational complexity of the proposed system
is analyzed, showing the feasibility of its real-time implementation.
Volume 2013
Journal name EURASIP Journal on Audio, Speech, and Music Processing
Publisher SpringerOpen, Springer-Verlag (Heidelberg, Germany)
Reference URL View reference page