• DocumentCode
    623618
  • Title

    EV-Human: Human localization via visual estimation of body electronic interference

  • Author

    Xinfeng Li ; Jin Teng ; Qiang Zhai ; Junda Zhu ; Dong Xuan ; Zheng, Yuan F. ; Wei Zhao

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA
  • fYear
    2013
  • fDate
    14-19 April 2013
  • Firstpage
    500
  • Lastpage
    504
  • Abstract
    Human localization is an enabling technology for many mobile applications. As more and more people carry mobile phones with them, we can now localize a person by localizing his mobile phone. However, it is observed that presence of human bodies introduces heavy interference to mobile phone signals. This has been one of the major causes of inaccurate wireless localization for humans. In this paper, we propose using video cameras to help estimate human body´s interference on mobile device´s signals. We combine human orientation detection and human/phone/AP relative position inference estimation to better measure how a human blocks or reflects wireless signals. We have also developed a signal distortion compensation model. Based on these technologies, we have implemented a human localization system called EV-Human. Real world experiments show that our EV-system can accurately and robustly localize humans.
  • Keywords
    mobile computing; mobile handsets; radiofrequency interference; video cameras; EV-Human; body electronic interference; human blocks; human bodies; human body interference estimation; human localization; human orientation detection; human-phone-AP relative position inference estimation; mobile device signals; mobile phone signals; signal distortion compensation model; video cameras; visual estimation; wireless localization; wireless signals; Biological system modeling; Cameras; Interference; Mobile communication; Mobile handsets; Visualization; Wireless communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INFOCOM, 2013 Proceedings IEEE
  • Conference_Location
    Turin
  • ISSN
    0743-166X
  • Print_ISBN
    978-1-4673-5944-3
  • Type

    conf

  • DOI
    10.1109/INFCOM.2013.6566823
  • Filename
    6566823