Automated Derivation of Primitives for Movement Classification

Abstract. We describe a new method for representing human movement compactly, in terms of a linear superimposition of simpler movements termed primitives. This method is a part of a larger research project aimed at modeling motor control and imitation using the notion of perceptuo-motor primitives, a basis set of coupled perceptual and motor routines. In our model, the perceptual system is biased by the set of motor behaviors the agent can execute. Thus, an agent can automatically classify observed movements into its executable repertoire. In this paper, we describe a method for automatically deriving a set of primitives directly from human movement data. We used movement data gathered from a psychophysical experiment on human imitation to derive the primitives. The data were first filtered, then segmented, and principal component analysis was applied to the segments. The eigenvectors corresponding to a few of the highest eigenvalues provide us with a basis set of primitives. These are...

• Type: Journal
• Year: 2002
• Where: AROBOTS
• Authors: Ajo Fod, Maja J. Mataric, Odest Chadwicke Jenkins
• Keywords: AROBOTS 2002, Human Movement, Larger Research Project, Perceptuo-motor Primitives