Real-time hand gesture recognition for service robot

Ke Wang*, Li Wang, Ruifeng Li, Lijun Zhao

*Corresponding author for this work

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

13 Citations (Scopus)

Abstract

A real-time hand gesture recognition system is developed for human-robot interaction of service robot. The proposed system is mainly composed of two subsystems: one for gesture recognition, and the other for the classification of the gesture motion. The system first uses a cascade classifier to locate the potential hand region from video frame. Then, Gabor wavelets transformation is applied to extract the gesture features which are automatically recognized based on a bank of Support Vector Machines (SVMs). For the estimated motion trajectory of each gesture, we make a set of discrete symbols using vector quantization method and, this symbol sequence is fed into the Hidden Markov Model (HMM) in the gesture motion classification subsystem. Experimental results are shown finally.

Original languageEnglish
Title of host publication2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010
Pages976-979
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010 - Changsha, China
Duration: 11 May 201012 May 2010

Publication series

Name2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010
Volume2

Conference

Conference2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010
Country/TerritoryChina
CityChangsha
Period11/05/1012/05/10

Keywords

  • Gabor ttransformation
  • Gesture recognition
  • Hidden markov model
  • Service robot
  • Support vector machine

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