Tech Report on Development of Gaze Following

[movellan]

The following report is available at http://mplab.ucsd.edu following
link to tech reports.
     
The Development of Gaze Following as a Bayesian 
        Systems Identification Problem

  Javier R. Movellan  & John S. Watson 
       UC San Diego      UC Berkeley                 

    UCSD's Institute for Neural Computation
  Machine Perception Lab Tech Report 2002.01



We propose a view of gaze following in which infants act as Bayesian
learners actively attempting to identify the operating characteristics
of the systems with which they interact.  We present results of an
experiment in which 28 infants (average age 10 months) interacted for a
3 minute period with a non-humanoid robot. For half the infants the
robot simulated contingency structure typically produced by human
beings. In particular it provided causal information about the existence
of a line of regard. For the other 14 infants, the robot behaved in a
manner which was not contingent with the environment. We found that a
few minutes of interaction with the contingent robot was sufficient to
elicit statistically detectable gaze following.  There were clear signs
that some of these infants were actively attempting to identify whether
or not the robot was responsive to them.  We propose that the infant
brain is equipped to learn and analyze the contingency structure of 
real-time social interactions.  Contingency is a fundamental perceptual 
dimension used by infants to recognize the operational properties of 
humans and to generalize  existing behaviors to new social partners.