• DocumentCode
    3311282
  • Title

    HMM based hand gesture recognition: A review on techniques and approaches

  • Author

    Moni, M.A. ; Ali, A. B M Shawkat

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Jatiya Kabi Kazi Nazrul Islam Univ., Bangladesh
  • fYear
    2009
  • fDate
    8-11 Aug. 2009
  • Firstpage
    433
  • Lastpage
    437
  • Abstract
    Gesture is one of the most natural and expressive ways of communications between human and computer in a virtual reality system. We naturally use various gestures to express our own intentions in everyday life. Hand gesture is one of the important methods of non-verbal communication for human beings for its freer in movements and much more expressive than any other body parts. Hand gesture recognition has a number of potential applications in human-computer interaction, machine vision, virtual reality, machine control in industry, and so on. As a gesture is a continuous motion on a sequential time series, the HMMs (hidden Markov models) must be a prominent recognition tool. The most important thing in hand gesture recognition is what the input features are that best represent the characteristics of the moving hand gesture.This paper presents part of literature review on ongoing research and findings on different technique and approaches in gesture recognition using HMMs for vision-based approach.
  • Keywords
    computer vision; gesture recognition; hidden Markov models; human computer interaction; image motion analysis; time series; virtual reality; HMM-based hand gesture recognition; continuous hand motion; expressive communication; hidden Markov model; human intention; human-computer interaction; industry machine control; machine vision; nonverbal communication; sequential time series; sign language recognition; virtual reality system; Australia; Cameras; Character recognition; Handicapped aids; Hidden Markov models; Humans; Image recognition; Natural languages; Virtual reality; Vocabulary; Hand gesture recognition; Hidden Markov Model; sign language recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4519-6
  • Electronic_ISBN
    978-1-4244-4520-2
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2009.5234536
  • Filename
    5234536