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Abstract: Comparison of two Gesture Recognition Sensors for Virtual TV Studios
Marina Ballester Ripoll, Jens Herder, Philipp Ladwig, and Kai Vermeegen, Comparison of two Gesture Recognition Sensors for Virtual TV Studios, GI-VRAR, Workshop Proceedings / Tagungsband: Virtuelle und Erweiterte Realität – 13. Workshop der GI-Fachgruppe VR/AR, ISBN 978-3-8440-4718-9, Bielefeld, September, 2016.
In order to improve the interactivity between users and computers, recent technologies focus on incorporating gesture recognition
into interactive systems. The aim of this article is to evaluate the effectiveness of using a Myo control armband and the Kinect 2
for recognition of gestures in order to interact with virtual objects in a weather report scenario. The Myo armband has an
inertial measurement unit and is able to read electrical activity produced by skeletal muscles, which can be recognized as gestures,
which are trained by machine learning. A Kinect sensor was used to build up a dataset which contains motion recordings of 8 different
gestures and was also build up by a gesture training machine learning algorithm. Both input methods, the Kinect 2 and the Myo armband,
were evaluated with the same interaction patterns in a user study, which allows a direct comparison and reveals benefits and limits of
each technique.
Keywords:
Gesture recognition, Interaction, Kinect, Myo, Virtual Studio, Machine learning
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