• Medientyp: E-Artikel
  • Titel: Hands-Free User Interface for AR/VR Devices Exploiting Wearer’s Facial Gestures Using Unsupervised Deep Learning
  • Beteiligte: Cha, Jaekwang; Kim, Jinhyuk; Kim, Shiho
  • Erschienen: MDPI AG, 2019
  • Erschienen in: Sensors
  • Sprache: Englisch
  • DOI: 10.3390/s19204441
  • ISSN: 1424-8220
  • Schlagwörter: Electrical and Electronic Engineering ; Biochemistry ; Instrumentation ; Atomic and Molecular Physics, and Optics ; Analytical Chemistry
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  • Beschreibung: <jats:p>Developing a user interface (UI) suitable for headset environments is one of the challenges in the field of augmented reality (AR) technologies. This study proposes a hands-free UI for an AR headset that exploits facial gestures of the wearer to recognize user intentions. The facial gestures of the headset wearer are detected by a custom-designed sensor that detects skin deformation based on infrared diffusion characteristics of human skin. We designed a deep neural network classifier to determine the user’s intended gestures from skin-deformation data, which are exploited as user input commands for the proposed UI system. The proposed classifier is composed of a spatiotemporal autoencoder and deep embedded clustering algorithm, trained in an unsupervised manner. The UI device was embedded in a commercial AR headset, and several experiments were performed on the online sensor data to verify operation of the device. We achieved implementation of a hands-free UI for an AR headset with average accuracy of 95.4% user-command recognition, as determined through tests by participants.</jats:p>
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