Comparison of two Gesture Recognition Sensors for Virtual TV Studios

  • 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.

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Metadaten
Author:Marina Ballester Ripoll, Jens HerderORCiDGND, Philipp Ladwig, Kai Vermeegen
Fachbereich/Einrichtung:Hochschule Düsseldorf
Hochschule Düsseldorf / Fachbereich - Medien
Document Type:Conference Proceeding
Year of Completion:2016
Language:English
Publisher:Shaker Verlag
Place of publication:Herzogenrath
Parent Title (English):GI-VRAR, Workshop Proceedings / Tagungsband: Virtuelle und Erweiterte Realität – 13. Workshop der GI-Fachgruppe VR/AR,
Editor:Thies Pfeiffer, Julia Fröhlich, Rolf Kruse
Related URL:http://vsvr.medien.hs-duesseldorf.de/publications/gi-vrar2016-gesture-abstract.html
ISBN:978-3-8440-4718-9
Tag:Gesture recognition; Interaction; Kinect; Myo; Virtual Studio
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
Licence (German):keine Lizenz - nur Metadaten
Release Date:2019/01/02