Air-writing for smart glasses by effective fingertip detection

Yung Han Chen, Po Chyi Su, Feng Tsun Chien

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This research investigates real-time fingertip detection in RGB images/frames captured from such wearable devices as smart glasses. A modified Mask Regional Convolutional Neural Network (Mask R-CNN) is proposed with one region-based CNN for hand detection and another three-layer CNN for locating the fingertip. The processing speed is high enough to facilitate several interesting applications. One application is to trace the location of a user's fingertip from first-person perspective to form writing trajectories. A text input mechanism for smart glasses can thus be implemented to enable a user to write letters/characters in air as the input and even interact with the system using simple gestures. Experimental results demonstrate the feasibility of this new text input methodology.

Original languageEnglish
Title of host publication2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages381-382
Number of pages2
ISBN (Electronic)9781728135755
DOIs
StatePublished - Oct 2019
Event8th IEEE Global Conference on Consumer Electronics, GCCE 2019 - Osaka, Japan
Duration: 15 Oct 201918 Oct 2019

Publication series

Name2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019

Conference

Conference8th IEEE Global Conference on Consumer Electronics, GCCE 2019
CountryJapan
CityOsaka
Period15/10/1918/10/19

Keywords

  • Air-writing
  • Fingertip
  • Mask R-CNN
  • Smart glasses

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