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Continuous micro finger writing recognition with a commodity smartwatch: demo abstract

Published:16 November 2020Publication History

ABSTRACT

Input is a significant problem for wearable devices, particularly for head-mounted virtual and augmented reality systems. Contemporary AR/VR systems use in-air gestures or handheld controllers for interactivity. However, mid-air handwriting provides a natural, subtle, and easy-to-use way to input commands and text. In this demo, we propose and investigate ViFin, a new technique for input commands and text entry which tracks continuous micro finger-level writing with a commodity smartwatch through vibrations. Inspired by the recurrent neural aligner and transfer learning, ViFin recognizes continuous finger writing and works across different users and achieves an accuracy of 90% and 91% for recognizing numbers and letters, respectively. Finally, a real-time writing system with two specific applications using AR smartglasses are implemented.

References

  1. Fang Hu, Peng He, Songlin Xu, Yin Li, and Cheng Zhang. 2020. FingerTrak: Continuous 3D Hand Pose Tracking by Deep Learning Hand Silhouettes Captured by Miniature Thermal Cameras on Wrist. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4, 2, Article 71 (June 2020), 24 pages.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Hong Li, Wei Yang, Jianxin Wang, Yang Xu, and Liusheng Huang. 2016. WiFinger: talk to your smart devices with finger-grained gesture. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp). 250--261.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Viet Nguyen, Siddharth Rupavatharam, Luyang Liu, Richard Howard, and Marco Gruteser. 2019. HandSense: capacitive coupling-based dynamic, micro finger gesture recognition. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems (SenSys). 285--297.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Siddharth S. Rautaray and Anupam Agrawal. 2015. Vision Based Hand Gesture Recognition for Human Computer Interaction: A Survey. Artif. Intell. Rev. 43, 1 (Jan. 2015), 1--54.Google ScholarGoogle ScholarCross RefCross Ref

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  1. Continuous micro finger writing recognition with a commodity smartwatch: demo abstract

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    • Published in

      cover image ACM Conferences
      SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems
      November 2020
      852 pages
      ISBN:9781450375900
      DOI:10.1145/3384419

      Copyright © 2020 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 16 November 2020

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      Overall Acceptance Rate174of867submissions,20%

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