Demo: SMART: screen-based gesture recognition on commodity mobile devices

Zimo Liao, Zhicheng Luo, Qianyi Huang*, Linfeng Zhang, Fan Wu, Qian Zhang, Yi Wang, Guihai Chen

*Corresponding author for this work

Research output: Contribution to journalConference article published in journalpeer-review

1 Citation (Scopus)

Abstract

In-air gesture control extends a touch screen and enables contactless interaction, thus has become a popular research direction in the past few years. Prior work has implemented this functionality based on cameras, acoustic signals, and Wi-Fi via existing hardware on commercial devices. However, these methods have low user acceptance. Solutions based on cameras and acoustic signals raise privacy concerns, while WiFi-based solutions are vulnerable to background noise. As a result, these methods are not commercialized and recent flagship smartphones have implemented in-air gesture recognition by adding extra hardware on-board, such as mmWave radar and depth camera. The question is, can we support in-air gesture control on legacy devices without any hardware modifications? In this demo, we design and implement SMART, an in-air gesture recognition system leveraging the screen and ambient light sensor (ALS), which are ordinary modalities on mobile devices. We implement SMART on a tablet. Results show that SMART can recognize 9 types of frequently used in-air gestures with an average accuracy of 96.1%.

Original languageEnglish
Pages (from-to)10-12
Number of pages3
JournalProceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM
DOIs
Publication statusPublished - 2021
Event27th ACM Annual International Conference On Mobile Computing And Networking, MobiCom 2021 - New Orleans, United States
Duration: 28 Mar 20221 Apr 2022

Bibliographical note

Publisher Copyright:
© 2021 Owner/Author.

Keywords

  • device-free
  • gesture recognition
  • non-intrusive visible communication
  • visible light sensing

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