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Gesture Classification with Hierarchically Structured Recurrent Self-Organizing Maps

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3 Author(s)
Baier, V. ; Univ. Munchen, Munich ; Mosenlechner, L. ; Kranz, M.

New input devices need clever algorithms to process input information. We constructed a hierarchically structured neural network assembly based on recurrent self-organizing maps which is able to process and to classify motion data. We derived motion data using a so called Gesture Cube (M. Kranz et al., 2006), a cubic tangible user interface developed for one-handed control of media appliances in a home environment. This previously recorded data was automatically pre-processed by our biologically inspired neural network and classified by a improved k-nearest neighborhood classifier. In this paper we shortly describe the platform used for data acquisition but focus on the novel algorithms used for classification.

Published in:

Networked Sensing Systems, 2007. INSS '07. Fourth International Conference on

Date of Conference:

6-8 June 2007