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The emergence of smartphones equipped with Internet access, high resolution cameras, and posi- tioning sensors opens up great opportunities for visualising geospatial information within augmented reality applications. While smartphones are able to provide geolocalisation, the inherent uncertainty in the estimated position, especially indoors, does not allow for completely accurate and robust alignment of the data with the camera images.
In this paper we present a system that exploits computer vision techniques in conjunction with GPS and inertial sensors to create a seamless indoor/outdoor positioning vision-based platform. The vision-based approach estimates the pose of the camera relative to the fac ̧ade of a building and recognises the fac ̧ade from a georeferenced image database. This permits the insertion of 3D widgets into the user’s view with a known orientation relative to the fac ̧ade. For example, in Figure 1 (a) we show how this feature can be used to overlay directional information on the input image. Furthermore we provide an easy and intuitive interface for non-expert users to add their own georeferenced content to the system, encouraging volunteering GI. Indeed, to achieve this users only need to drag and drop predefined 3D widgets into a reference view of the fac ̧ade, see Figure 1 (b). The infrastructure is flexible in that we can add different layers of content on top of the fac ̧ades and hence, this opens many possibilities for different applications. Furthermore the system provides a representation suitable for both manual and automatic content authoring.
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