M.I.T. Media Laboratory Perceptual Computing Group Technical Report No.
364.
Task-specific Gesture Analysis in Real-Time using Interpolated Views
Trevor J. Darrell, Irfan A. Essa, Alex P. Pentland
Hand and face gestures are modeled using an appearance-based approach in
which patterns are represented as a vector of similarity scores to a {\sl
set} of view models defined in space and time. These view models are learned
from examples using unsupervised clustering techniques. A supervised learning
paradigm is used to interpolate view scores into a task-dependent coordinate
system appropriate for recognition and control tasks. We apply this analysis
to the problem of context-specific gesture interpolation and recognition,
and demonstrate real-time systems which perform these tasks.
A Postscript
version of this report is available.