@inproceedings{INSS07C, author = {V Baier and L M\"{o}senlechner and Matthias Kranz}, title = {{Gesture Classification with Hierarchically Structured Recurrent Self-Organizing Maps}}, year = {2007}, month = {Mar}, abstract = {{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.}}, booktitle = {Proc. Fourth International Conference on Networked Sensing Systems INSS '07}, doi = {10.1109/INSS.2007.4297394}, pages = {81--84}, }