FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMAS

Location-based services (LBS) on web-based maps and images have come into real-time since Google launched its Street View imaging services in 2007. This research employs Google Maps API and Web Service, GAE for JAVA, AJAX, Proj4js, CSS and HTML in developing an internet platform for accessing the or...

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Main Authors: V. J. D. Tsai, C.-T. Chang
Format: Article
Language:English
Published: Copernicus Publications 2012-07-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-4/305/2012/isprsannals-I-4-305-2012.pdf
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spelling doaj-7f842da6d3284095b9ddbe648ff25eb42020-11-25T01:45:11ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502012-07-01I-430530910.5194/isprsannals-I-4-305-2012FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMASV. J. D. Tsai0C.-T. Chang1Dept. of Civil Engineering, National Chung Hsing University, Taichung 40227, TaiwanDept. of Civil Engineering, National Chung Hsing University, Taichung 40227, TaiwanLocation-based services (LBS) on web-based maps and images have come into real-time since Google launched its Street View imaging services in 2007. This research employs Google Maps API and Web Service, GAE for JAVA, AJAX, Proj4js, CSS and HTML in developing an internet platform for accessing the orientation parameters of Google Street View (GSV) panoramas in order to determine the three dimensional position of interest features that appear on two overlapping panoramas by geometric intersection. A pair of GSV panoramas was examined using known points located on the Library Building of National Chung Hsing University (NCHU) with the root-mean-squared errors of ±0.522m, ±1.230m, and ±5.779m for intersection and ±0.142m, ±1.558m, and ±5.733m for resection in X, Y, and h (elevation), respectively. Potential error sources in GSV positioning were analyzed and illustrated that the errors in Google provided GSV positional parameters dominate the errors in geometric intersection. The developed system is suitable for data collection in establishing LBS applications integrated with Google Maps and Google Earth in traffic sign and infrastructure inventory by adding automatic extraction and matching techniques for points of interest (POI) from GSV panoramas.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-4/305/2012/isprsannals-I-4-305-2012.pdf
collection DOAJ
language English
format Article
sources DOAJ
author V. J. D. Tsai
C.-T. Chang
spellingShingle V. J. D. Tsai
C.-T. Chang
FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMAS
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet V. J. D. Tsai
C.-T. Chang
author_sort V. J. D. Tsai
title FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMAS
title_short FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMAS
title_full FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMAS
title_fullStr FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMAS
title_full_unstemmed FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMAS
title_sort feature positioning on google street view panoramas
publisher Copernicus Publications
series ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 2194-9042
2194-9050
publishDate 2012-07-01
description Location-based services (LBS) on web-based maps and images have come into real-time since Google launched its Street View imaging services in 2007. This research employs Google Maps API and Web Service, GAE for JAVA, AJAX, Proj4js, CSS and HTML in developing an internet platform for accessing the orientation parameters of Google Street View (GSV) panoramas in order to determine the three dimensional position of interest features that appear on two overlapping panoramas by geometric intersection. A pair of GSV panoramas was examined using known points located on the Library Building of National Chung Hsing University (NCHU) with the root-mean-squared errors of ±0.522m, ±1.230m, and ±5.779m for intersection and ±0.142m, ±1.558m, and ±5.733m for resection in X, Y, and h (elevation), respectively. Potential error sources in GSV positioning were analyzed and illustrated that the errors in Google provided GSV positional parameters dominate the errors in geometric intersection. The developed system is suitable for data collection in establishing LBS applications integrated with Google Maps and Google Earth in traffic sign and infrastructure inventory by adding automatic extraction and matching techniques for points of interest (POI) from GSV panoramas.
url http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-4/305/2012/isprsannals-I-4-305-2012.pdf
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