Analysis, Interpretation and Synthesis of Facial Expressions
Irfan A. Essa
Ph. D. Thesis Submitted to Program in Media Arts & Sciences, MIT
Media Laboratory, Sept. 1994
This thesis describes a computer vision system for observing the
``action units'' of a face using video sequences as input. The visual
observation (sensing) is achieved by using an optimal estimation
optical flow method coupled with a geometric and a physical (muscle)
model describing the facial structure. This modeling results in a
time-varying spatial patterning of facial shape and a parametric
representation of the independent muscle action groups responsible for
the observed facial motions. These muscle action patterns are then
used for analysis, interpretation, recognition, and synthesis of
facial expressions. Thus, by interpreting facial motions within a
physics-based optimal estimation framework, a new control model of
facial movement is developed. The newly extracted action units (which
we name ``FACS+'') are both physics and geometry-based, and extend
the well known FACS parameters for facial expressions by adding
temporal information and non-local spatial patterning of facial
motion.
Also available as MIT Media Laboratory, Vision and Modeling Group
Technical Report # 303
Compressed ASCII PostScript 9.385 MegaBytes File
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Irfan A. Essa (1994)
TR#303: Analysis, Interpretation and Synthesis of Facial
Expressions [9385 kBytes], Ph. D. Thesis, Massachusetts Institute of Technology, Cambridge, MA. 1994.
Irfan Essa, irfan@media.mit.edu
Last modified: Thu Feb 15 10:29:53 EST 1996