• DocumentCode
    2391830
  • Title

    Fingertip tracking and multi-point gesture recognition

  • Author

    Wensheng, Li ; Huaiwen, He

  • Author_Institution
    Zhongshan Inst., Univ. of Electron. Sci. & Technol. of China, Zhongshan, China
  • fYear
    2010
  • fDate
    6-8 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents a method of multi-point gesture recognition based on machine vision, which can achieve similar features of multi-touch like iPhone with a camera. Firstly we present a CamShift based method to track fingertips, then we present a method of multi-point gesture recognition based on BP neural network. The method was realized and tested through DirectShow, and results show that the proposed methods are reliable and efficient for the tracking of fingertips and for the recognition of multi-point gestures.
  • Keywords
    backpropagation; computer vision; gesture recognition; neural nets; BP neural network; fingertip tracking; iPhone; machine vision; multipoint gesture recognition; Artificial neural networks; Fingers; Gesture recognition; Image color analysis; Mice; Signal processing algorithms; Target tracking; BP Neural Network; CamShift algorithm; Machine Vision; Multi-Point Gesture Recognition; Tracking of Fingertip;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Signal Processing and Communication Systems (ISPACS), 2010 International Symposium on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-7369-4
  • Type

    conf

  • DOI
    10.1109/ISPACS.2010.5704778
  • Filename
    5704778
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2391830