Robot user control system using hand gesture recognizer

Suwon Shon, Jounghoon Beh, Cheoljong Yang, Han Wang, Hanseok Ko

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


This paper proposes a robot control human interface using Markov model (HMM) based hand signal recognizer. The command receiving humanoid robot sends webcam images to a client computer. The client computer then extracts the intended commanding human's hand motion descriptors. Upon the feature acquisition, the hand signal recognizer carries out the recognition procedure. The recognition result is then sent back to the robot for responsive actions. The system performance is evaluated by measuring the recognition of '48 hand signal set' which is created randomly using fundamental hand motion set. For isolated motion recognition, '48 hand signal set' shows 97.07% recognition rate while the 'baseline hand signal set' shows 92.4%. This result validates the proposed hand signal recognizer is indeed highly discernable. For the '48 hand signal set' connected motions, it shows 97.37% recognition rate. The relevant experiments demonstrate that the proposed system is promising for real world human-robot interface application.

Original languageEnglish
Pages (from-to)368-374
Number of pages7
JournalJournal of Institute of Control, Robotics and Systems
Issue number4
Publication statusPublished - 2011 Apr


  • HMM
  • Hand gesture
  • Robot control system

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Applied Mathematics


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