Abstract
This paper introduces a system for gesture based interaction with smart
environments. The framework we present connects gesture recognition results with
control commands for appliances in a smart home that are accessed through a middleware
based on the ISO 24752 standard URC (Universal Remote Console). Gesture
recognition is realized by applying three dimensional acceleration sensor information
of the WiiMote from Nintendo. This information is trained to a toolkit for
gesture recognition that implements machine learning algorithms well known from
speech recognition. Our study focuses on two interaction concepts with the aim to
exploit the context and special home scenarios. This serves to reduce the number of
gestures while in parallel retaining the control complexity on a high level. A user
test, also with older persons, compares both concepts and evaluates their efficiency
by observing the response times and the subjective impressions of the test persons.
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