J Acoust Soc Am. 2005 Jul;118(1):405-9.

Empirical modeling of human face kinematics during speech using motion clustering.

Lucero JC, Maciel ST, Johns DA, Munhall KG.

Source

Department of Mathematics, University of Brasilia, Brasilia DF 70910-900, Brazil. lucero@mat.unb.br

Abstract

In this paper we present an algorithm for building an empirical model of facial biomechanics from a set of displacement records of markers located on the face of a subject producing speech. Markers are grouped into clusters, which have a unique primary marker and a number of secondary markers with an associated weight. Motion of the secondary markers is computed as the weighted sum of the primary markers of the clusters to which they belong. This model may be used to produce facial animations, by driving the primary markers with measured kinematic signals.

PMID:: 16119361; [PubMed - indexed for MEDLINE]

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DC-05774/DC/NIDCD NIH HHS/United States

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Analysis of facial motion patterns during speech using a matrix factorization algorithm. [J Acoust Soc Am. 2008]
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Cited by 1 PubMed Central article

Analysis of facial motion patterns during speech using a matrix factorization algorithm. [J Acoust Soc Am. 2008]
Analysis of facial motion patterns during speech using a matrix factorization algorithm.
Lucero JC, Munhall KG. J Acoust Soc Am. 2008 Oct; 124(4):2283-90.

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