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Decomposition of Human Motion into Dynamics Based Primitives with Application to Drawing Tasks |
Abstract |
Using tools from dynamical systems and sys … Using tools from dynamical systems and systems identification we develop a framework for the study
of primitives for human motion, which we refer to as movemes. The objective is understanding human
motion by decomposing it into a sequence of elementary building blocks that belong to a known alphabet
of dynamical systems. In this work we address the problem of defining conditions under which
collections of signals are well-posed according to a dynamical model class M and then can generate
movemes. Based on the assumption of well-posedness, we develop segmentation and classification algorithms
in order to reduce a complex activity into the sequence of movemes that have generated it.
Using examples we show that the definition of well-posedness can be applied in practice and show
analytically that the proposed algorithms are robust with respect to noise and model uncertainty. We
test our ideas on data sampled from five human subjects who were drawing figures using a computer
mouse. Our experiments show that we are able to distinguish between movemes and recognize them
even when they take place in activities containing more than one moveme at a time. containing more than one moveme at a time. +
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Authors | D. Del Vecchio, R. M. Murray and P. Perona + |
ID | 2002f + |
Source | <i>Automatica</i>, 39(12):2085-2098 + |
Tag | dmp03-automatica + |
Title | Decomposition of Human Motion into Dynamics Based Primitives with Application to Drawing Tasks + |
Type | Preprint + |
Categories | Papers |
Modification date This property is a special property in this wiki.
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15 May 2016 06:19:01 + |
URL This property is a special property in this wiki.
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http://www.cds.caltech.edu/~murray/preprints/dmp03-automatica.pdf + |
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Decomposition of Human Motion into Dynamics Based Primitives with Application to Drawing Tasks + | Title |
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