On Learning the Shape of Complex Actions

Authors:
Terry Caelli;Andrew McCabe;Gordon Binsted
Affiliations:
-;-;-
Venue:
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Year:
2001

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Abstract

In this paper we show how the shape and dynamics of complex actions can be encoded using the intrinsic curvature and torsion signatures of their component actions. We then show how such invariant signatures can be integrated into a Dynamical Bayesian Network which compiles efficient recurrent rules for predicting and recognizing complex actions. An application in skill analysis is used to illustrate our approach.