Gesture Classification with Hierarchically Structured Recurrent Self-Organizing Maps

Volker Baier, Lorenz Mosenlechner, Matthias Kranz
2007 2007 Fourth International Conference on Networked Sensing Systems  
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 [1], 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
more » ... work 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.
doi:10.1109/inss.2007.4297394 fatcat:nxrgqsnzwfhqrpfuus5b3yio7q