Wearable air-writing recognition system employing dynamic time warping

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Gesture recognition has been a popular research field under the trend of IoT and intelligent devices. Air-writing is the most challenging and crucial topic in the gesture recognition field. In this paper, we propose a wearable air-writing system that makes users can write the English alphabet in the three-dimensional space without any write rules. The proposed system is based on the Inertial Measurement Unit (IMU), and it uses dynamic time warping (DTW) as the main recognition algorithm. In addition, to improve the recognition accuracy and take a better advantage of the DTW algorithm, we present an adjustment system that gives some new optimization methods to the application of IMU and DTW. In the experiment, the accuracy of recognition is 84.6% for the uppercase alphabet (from 'A' to 'Z') in user-dependent case. And we also confirmed that the recognition method only based on the DTW algorithm is one kind of user-dependent methods, which means this method is heavily dependent on personalization.

Original languageEnglish
Title of host publication2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728197944
DOIs
Publication statusPublished - 2021 Jan 9
Event18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021 - Virtual, Las Vegas, United States
Duration: 2021 Jan 92021 Jan 13

Publication series

Name2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021

Conference

Conference18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021
CountryUnited States
CityVirtual, Las Vegas
Period21/1/921/1/13

Keywords

  • Air-writing
  • Dynamic time warping
  • Gesture recognition
  • Human computer interaction
  • IMU
  • Wearable devices

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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