• DocumentCode
    4557
  • Title

    Potential Accuracy of Traffic Signs´ Positions Extracted From Google Street View

  • Author

    Wai Yeung Yan ; Shaker, Ahmed ; Easa, S.

  • Author_Institution
    Dept. of Civil Eng., Ryerson Univ., Toronto, ON, Canada
  • Volume
    14
  • Issue
    2
  • fYear
    2013
  • fDate
    Jun-13
  • Firstpage
    1011
  • Lastpage
    1016
  • Abstract
    This work demonstrates the potential use of Google Street View (GSV) in engineering measurements. An investigation was conducted to assess the geopositioning accuracy of traffic signs extracted from GSV. A direct linear transformation (DLT) model is used to establish the relationship between the GSV image coordinate system and the ground coordinate system with the aid of ground control points (GCPs). The ground coordinates of the traffic sign can be retrieved by using the solved DLT coefficients. It is found that the root-mean-square (RMS) error of the extracted traffic sign´s location is less than 1 m in general. By increasing the number of GSV images and GCPs, the RMS error can be further reduced to 0.5 m or less. This preliminary study demonstrates a viable solution to extract the location of traffic signs from GSV.
  • Keywords
    cartography; traffic engineering computing; DLT coefficients; DLT model; GCP; GSV; GSV image coordinate system; Google street view; RMS error; direct linear transformation model; engineering measurements; geopositioning accuracy; ground control points; ground coordinate system; root-mean-square error; traffic sign position; Accuracy; Cameras; Computational modeling; Feature extraction; Google; Roads; Direct linear transformation (DLT); Google Street View (GSV); ground control points (GCPs); traffic sign;
  • fLanguage
    English
  • Journal_Title
    Intelligent Transportation Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1524-9050
  • Type

    jour

  • DOI
    10.1109/TITS.2012.2234119
  • Filename
    6408202