Three‐dimensional positioning from Google street view panoramas. Issue 3 (1st April 2013)

• Record Type: Journal Article
• Authors: Tsai, Victor J.D.; Chang, Chun‐Ting
• Is Part Of: IET image processing. Volume 7:Issue 3(2013)
• Page Start: 229
• Page End: 239
• Publication Date: 2013-04-01
• Subjects: application program interfaces -- geographic information systems -- hypermedia markup languages -- Java -- mobile computing -- Web services -- social networking (online); three‐dimensional positioning -- Google street view panoramas -- location‐based services -- LBS -- Web‐based maps -- Google Maps API -- Web service -- GAE -- JAVA -- AJAX -- Proj4js -- HyperText markup language -- points of interest -- POI -- GSV images -- National Chung Hsing University; application program interfaces -- geographic information systems -- hypermedia markup languages -- Java -- mobile computing -- Web services -- social networking (online); three‐dimensional positioning -- Google street view panoramas -- location‐based services -- LBS -- Web‐based maps -- Google Maps API -- Web service -- GAE -- JAVA -- AJAX -- Proj4js -- HyperText markup language -- points of interest -- POI -- GSV images -- National Chung Hsing University; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2012.0323
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : 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, cascading style sheets and HyperText markup language in developing a platform for accessing the orientation parameters of Google street view (GSV) panoramas in order to determine the three‐dimensional (3D) position of points of interest (POIs) by intersection between two nearby GSV images and to validate the 3D position of a GSV panorama by resection from three known POIs. Extracted 3D positional information of the features are then packed in keyhole markup language format and stored in GAE Servlet for future LBS applications integrated with Google Maps and Google Earth. Experimental results from two tests on intersection and one test on resection of GSV panoramas in National Chung Hsing University campus were examined with error reports and source analyses. With automatic conjugate image‐matching capability, the developed system is suitable for volumetric data collection in establishing web‐based LBS applications integrated with GSV panoramas and Google Maps/Earth in which positional accuracy is not primarily concerned.