A hybrid computer vision and Wi-Fi Doppler radar system for capturing the 3-D hand gesture trajectory with a smartphone

Mu Cyun Tang, Chien Lun Chen, Min Hui Lin, Fu Kang Wang, Chia Hung Yeh, Tzyy Sheng Horng

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

Abstract

This paper presents a 3-D hand gesture capture technique using the 2D camera and Wi-Fi connection signals of a smartphone. The motion detection principle of this technique involves combining the algorithm of pixel-based computer vision and the extraction of Doppler shift from the reflected Wi-Fi signals. Moreover, a joint displacement calibration procedure is proposed to transform the camera pixel coordinates to the radar space coordinates. This technique has the advantages of lower computation resources and power consumption than the current counterparts and requires no extra cameras and RF transmission sources when used on a smartphone.

Original languageEnglish
Title of host publication2017 IEEE MTT-S International Microwave Symposium, IMS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1251-1254
Number of pages4
ISBN (Electronic)9781509063604
DOIs
Publication statusPublished - 2017 Oct 4
Externally publishedYes
Event2017 IEEE MTT-S International Microwave Symposium, IMS 2017 - Honololu, United States
Duration: 2017 Jun 42017 Jun 9

Publication series

NameIEEE MTT-S International Microwave Symposium Digest
ISSN (Print)0149-645X

Conference

Conference2017 IEEE MTT-S International Microwave Symposium, IMS 2017
Country/TerritoryUnited States
CityHonololu
Period2017/06/042017/06/09

Keywords

  • 3-D hand gesture detection
  • Hybrid motion detection system
  • Pixel-based computer vision
  • Wi-Fi Doppler radar

ASJC Scopus subject areas

  • Radiation
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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