• DocumentCode
    2670131
  • Title

    Hand gesture recognition for automatic tap system

  • Author

    Ullah, Sadiq ; Saman, Gule ; Khan, Farid

  • Author_Institution
    Dept. of Comput. Sci., GIK Inst. of Eng. Topi, Topi, Pakistan
  • fYear
    2015
  • fDate
    25-26 March 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents a technique for real time human hand gesture recognition system for automatic tap operation. Hand gesture recognition based machines have been widely developed in recent years. Most of the techniques use skin color models due to its robustness and simplicity. In this work there are two major steps for achieving this goal: firstly, the detection of skin color and secondly, the classification of a gesture into valid and invalid hand gesture for the operation of the water tap. The proposed system uses Support Vector Machine and neural network for classification of the hand gesture which in turn operates the tap.
  • Keywords
    gesture recognition; image classification; image colour analysis; neural nets; support vector machines; automatic tap operation; automatic tap system; hand gesture classification; hand gesture recognition based machines; neural network; real time human hand gesture recognition system; skin color detection; skin color models; support vector machine; Artificial neural networks; Cameras; Gesture recognition; Image color analysis; Lighting; Skin; Support vector machines; Gesture recognition; Neural Networks; RGB; SVM; YCbCr; color constancy; connected neighborhood mechanism; illumination compensation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Computer Vision (ISCV), 2015
  • Conference_Location
    Fez
  • Print_ISBN
    978-1-4799-7510-5
  • Type

    conf

  • DOI
    10.1109/ISACV.2015.7106176
  • Filename
    7106176