Multiple fingertip detection under single camera with human computer interface applications

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

Abstract

This work proposes an accurate marker-less fingertip detection method under single camera. The moving skin regions are analyzed via enhanced mixture models. The models with adaptive learning rates can separate the backgrounds and moving skins effectively. For multiple fingertip detection, we propose an algorithm based on the likelihood computation of contour and curvature information. Furthermore, finger width validation and error correction via temporal information is used to improve the detection accuracy. The experiments have shown that the proposed method is robust and flexible. Finally, we implement a human computer interface system to test the effectiveness of the proposed framework.

Original languageEnglish
Title of host publication2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509023332
DOIs
StatePublished - 27 Dec 2016
Event5th IEEE Global Conference on Consumer Electronics, GCCE 2016 - Kyoto, Japan
Duration: 11 Oct 201614 Oct 2016

Publication series

Name2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016

Conference

Conference5th IEEE Global Conference on Consumer Electronics, GCCE 2016
Country/TerritoryJapan
CityKyoto
Period11/10/1614/10/16

Keywords

  • Enhanced Mixture Models
  • Fingertip Detection
  • Human Computer Interface
  • Skin Region Analysis

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