Abstract
This paper concerns virtual reality (VR) environments and innovative, natural interaction techniques for them. The presented research was driven by the goal to enable users to invoke actions with their body physically, causing the correct action of the VR environment. The paper introduces a system that tracks a user’s movements that are recognized as specific gestures. Smartwatches are promising new devices enabling new modes of interaction. They can support natural, hands-free interaction. The presented effort is concerned with the replacement of common touch input gestures with body movement gestures. Missing or insufficiently precise sensor data are a challenge, e.g., gyroscope and magnetometer data. This data is needed, together with acceleration data, to compute orientation and motion of the device. A transformation of recorded smartwatch data to arm movement gestures is introduced, involving data smoothing and gesture state machines.
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Acknowledgments
This research was funded by the German research foundation (DFG) within the IRTG 2057 “Physical Modeling for Virtual Manufacturing Systems and Processes”.
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Rupprecht, F., Heck, B., Hamann, B., Ebert, A. (2019). Signal-Processing Transformation from Smartwatch to Arm Movement Gestures. In: Nunes, I. (eds) Advances in Human Factors and Systems Interaction. AHFE 2018. Advances in Intelligent Systems and Computing, vol 781. Springer, Cham. https://doi.org/10.1007/978-3-319-94334-3_13
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DOI: https://doi.org/10.1007/978-3-319-94334-3_13
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