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A prototype for automatic recognition of spontaneous facial actions
A prototype for automatic recognition of
spontaneous facial actions
M.S. Bartlett, G. Littlewort, B. Braathen, T.J. Sejnowski
, and J.R. Movellan
Institute for Neural Computation
and Department of Biology
University of California, San Diego
and Howard Hughes Medical Institute at the Salk Institute
Email: marni, gwen, bjorn, terry, javier @inc.ucsd.edu
Abstract
We present ongoing work on a project for automatic recognition of spon-
taneous facial actions. Spontaneous facial expressions differ substan-
tially from posed expressions, similar to how continuous, spontaneous
speech differs from isolated words produced on command. Previous
methods for automatic facial expression recognition assumed images
were collected in controlled environments in which the subjects delib-
erately faced the camera. Since people often nod or turn their heads,
automatic recognition of spontaneous facial behavior requires methods
for handling out-of-image-plane head rotations. Here we explore an ap-
proach based on 3-D warping of images into canonical views. We eval-
uated the performance of the approach as a front-end for a spontaneous
expression recognition system using support vector machines and hidden
Markov models. This system employed general purpose learning mech-
anisms that can be applied to recognition of any facial movement. The
system was tested for recognition of a set of facial actions defined by
the Facial Action Coding System (FACS). We showed that 3D tracking
and warping followed by machine learning techniques directly applied to
the warped images, is a viable and promising technology for automatic
facial expression recognition. One exciting aspect of the approach pre-
sented here is that information about movement dynamics emerged out
of filters which were derived from the statistics of images.
1 Introduction
Much of the early work on computer vision applied to facial expressions focused on rec-
ognizing a few prototypical expressions of emotion produced on command
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