Augmented Reality (AR) offers a means to inject virtual information into real scenes. In the past few years, AR has been receiving greater attention thanks to considerable advancements in the hardware of consumer-level portable devices. In this paper, we illustrate how mobile AR can be exploited to intuitively visualize, and moreover generate new, geo-data. We explore these two concepts through i) the visualization and interaction modality of geo-data as AR layers and ii) the exploitation of mobile devices as opportunistic sensors for generating information relating to a user's immediate surroundings.

With respect to satellite and aerial RGB images, ground-based acquisitions can provide a more detailed representation of a natural landscape, especially for steep slopes. Moreover, for some applications the generation of a new `virtual' view-point can provide a valuable visualization tool. Using such a technique, the visual appearance of a landscape (generated from one or several geo-registered images) can be seen from a new, specified vantage point. In this paper, we propose a method of generating a visual appearance model and subsequent virtual views, through a direct re-projection of visual content from source geo-registered images.

This paper presents a system to create a spatiotemporal attractiveness GIS layer for mountainous areas brought about by the implementation of novel image processing and pattern matching algorithms. We utilize the freely available Digital Terrain Model of the planet provided by NASA [1] to generate a three-dimensional synthetic model around a viewer's location. Using an array of image processing algorithms we then align photographs to this model. We will demonstrate the accuracy of the resulting system through the overlaying of geo-referenced content, such as mountain names and then we will suggest ways in which visitors/photographers can exploit the results of this research, such as suggesting temporally appropriate photo-hotspots close to their current location.

The MEMORI system automatically detects and recognizes rescaled and/or rotated versions of objects from a database within digital color images with cluttered background. This paper describes the system's architecture and the methods implemented within, and its use as a tool for the automatic annotation and browsing of digital images of web furniture catalogs.