Machine perception primitives for real time social interaction
Fortenberry, B., Bartlett, M.S., Roddey, J.C., Fasel, I., Marks, T., Littlewort, G., Chenu, J., Movellan, J.R.
Demonstration
18th Conference on Neural Information Processing Systems
Vancouver, Canada. December 13-16, 2004.
Abstract
We present four demonstrations of primitives for real-time social
interaction. (1) Facial Expression Recognition: using a texture-based
recognition system that employs Gabor wavelet decomposition and support
vector machines, we can recogniz e 7 expressions of basic emotion as well
as 18 action units from the Facial Acti on Coding System (FACS). (2)
Real-Time Unsupervised Object Learning: we present a generative approach
for performing unsupervised learning and tracking of faces . (3) G-flow:
using a stochastic filtering algorithm based on a conditionally Ga ussian
generative model, we track in 3D the rigid and non-rigid motion of a face
from 2D video. (4) Infomax Controller for Social Contingency Detection: we
pres ent a humanoid robot that implements an optimal Bayesian
controller. The control ler schedules the robot's behavior in real time to
maximize the speed and accura cy of detection of the presence of people.