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
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