Annotating Gigapixel Images

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Summary:
Qing Luan, et al. present their developments in the annotation of very large (billions of pixels or gigapixel) images in this paper.  Their aim was to augment the pan-and-zoom interface used by applications like Google Earth and Virtual Earth with visual and audio annotations, driven by an intelligent rendering system that takes into account the viewer's perceptual distance from the objects being annotated.  They mentioned related work in areas like zoomable UIs, map labeling, human psychophysics, and augmented reality systems.  The system developed by the researchers runs on HD View and consists of text labels, audio loops, or narrative audio.

The system gauges viewer perspective, depth, and field of view relative to each annotation; it then assigns strengths to the various annotations based on these elements.  Thus, farther-off text labels will be smaller or farther-off audio annotations will be played at lower volume.


Discussion:
I haven't played with Google Earth very much, but according to the authors this system is a lot like it, so I think I have a pretty good idea of how the interface works.  I think it's a great idea to render annotations dynamically based on viewer position -- if all available annotations were rendered simultaneously on a map of the United States it would be completely unreadable.  Hiding or showing labels as the user pans and zooms encourages the user to explore the image to see what annotations can be uncovered.  This would be great if applied to an educational setting where children could browse a map of, say, Philadelphia and read excerpts from historical documents or hear audio clips about important locations.