• DocumentCode
    2077112
  • Title

    Recognition of hand gesture using hidden Markov model

  • Author

    Irteza, Khan Mohammad ; Ahsan, Sk Md Masudul ; Deb, Razib Chandra

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Khulna Univ. of Eng. & Technol., Khulna, Bangladesh
  • fYear
    2012
  • fDate
    22-24 Dec. 2012
  • Firstpage
    150
  • Lastpage
    154
  • Abstract
    In this paper we proposed a recognition system for hand gesture in 3D environment by using only a single camera. For calculating the relative motion towards the camera, generally a depth sensing device is needed. In order to remove that, we proposed an approach of using the change of the area of the hand in input image. Using skin color; we detect the hand from the input image sequences and then we process the data for feature extraction. Three features are proposed for effectively recognize the gesture by our system. These are orientation, area and angle of the palm. As we proposed our system for dynamic gesture, Hidden Markov Model is utilized to recognize the gesture. In our lab environment our proposed system shows very promising result and we were able to achieve about 80.67% recognition rate on average. The system that we proposed will not only help to recognize the gesture of hand accurately but also lessen the cost for implementing this kind of system because of using minimal number of hardware.
  • Keywords
    feature extraction; gesture recognition; hidden Markov models; image colour analysis; image motion analysis; image sequences; depth sensing device; dynamic gesture; feature extraction; hand detection; hand gesture recognition; hidden Markov model; image sequence; relative motion calculation; skin color; Computer vision; Hidden Markov models; Human computer interaction; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology (ICCIT), 2012 15th International Conference on
  • Conference_Location
    Chittagong
  • Print_ISBN
    978-1-4673-4833-1
  • Type

    conf

  • DOI
    10.1109/ICCITechn.2012.6509747
  • Filename
    6509747