Title: Using clustering techniques for intelligent camera-based user interfaces
Authors: Zorana Bankovic; Jose M. Moya; Elena Romero; Javier Blesa; David Fraga; Juan Carlos Vallejo; Alvaro Araujo; Pedro Malagon; Juan-Mariano De Goyeneche; Daniel Villanueva; Octavio Nieto-Taladriz
Published in: Logic Journal of IGPL 2011, Vol 19, 1
ISSN : 1368-9894
Date of Publication: February 2011
Digital Object Identifier : 10.1093/jigpal/jzr008
Web: http://jigpal.oxfordjournals.org/content/early/2011/02/08/jigpal.jzr008.refs

The area of Human–Machine Interface is growing fast due to its high importance in all technological systems. The basic idea behind designing human–machine interfaces is to enrich the communication with the technology in a natural and easy way. Gesture interfaces are a good example of transparent interfaces. Such interfaces must identify properly the action the user wants to perform, so the proper gesture recognition is of the highest importance. However, most of the systems based on gesture recognition use complex methods requiring high-resource devices. In this work, we propose to model gestures capturing their temporal properties, which significantly reduce storage requirements, and use clustering techniques, namely self-organizing maps and unsupervised genetic algorithm, for their classification. We further propose to train a certain number of algorithms with different parameters and combine their decision using majority voting in order to decrease the false positive rate. The main advantage of the approach is its simplicity, which enables the implementation using devices with limited resources, and therefore low cost. The testing results demonstrate its high potential.