• DocumentCode
    2255590
  • Title

    Heading change detection for indoor navigation with a Smartphone camera

  • Author

    Ruotsalainen, Laura ; Kuusniemi, Heidi ; Chen, Ruizhi

  • Author_Institution
    Dept. of Navig. & Positioning, Finnish Geodetic Inst., Masala, Finland
  • fYear
    2011
  • fDate
    21-23 Sept. 2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    A comfortable and useful pedestrian navigation system is accurate, reasonably priced, easy to use, and light to carry. Smartphones are attractive platforms for the navigation systems due to their small size, low cost, and the fact that they are already carried routinely by many pedestrians. Pedestrian navigation is mostly needed in GNSS degraded and denied areas such as indoors and in urban canyons. Positioning in these environments is still a challenging task. Aiding from other location sensors is typically needed. Obtaining a reliable heading e.g. from a digital compass is one of the most challenging tasks indoors because of the environmental disturbances to the sensor measurements. Visual-aiding has been considered for solving this problem for the last few years. Most algorithms are however often too massive for a Smartphone with limited computing power and storage space. This paper presents a lightweight algorithm for solving the problem. It is based on vanishing points calculated from lines in consecutive images. Results from a field test with a Nokia Smartphone have demonstrated that the performance of the algorithm in calculating the heading change is much better than that of the built-in digital compass. The heading change can be detected with the proposed algorithm at about 1 Hz frequency under the PC environment. It has potential to be adopted for a Smartphone platform.
  • Keywords
    cameras; image processing; mobile handsets; navigation; object detection; GNSS; Smartphone camera; digital compass; heading change detection; indoor navigation; pedestrian navigation system; vanishing points; visual aiding; Cameras; Compass; Image edge detection; Maximum likelihood detection; Navigation; Noise; Sensors; Indoor; Navigation; Pedestrian; Smartphone; Visual-aiding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Indoor Positioning and Indoor Navigation (IPIN), 2011 International Conference on
  • Conference_Location
    Guimaraes
  • Print_ISBN
    978-1-4577-1805-2
  • Electronic_ISBN
    978-1-4577-1803-8
  • Type

    conf

  • DOI
    10.1109/IPIN.2011.6071924
  • Filename
    6071924