Paige and I have a small project called ImageWiki which lets you search for images that are similar to other images. We find it interesting because searching for images is political. "In the future" our Augmented Reality views will translate images into extended meta-data and it seems important to have us all own that meta-data rather than any one company.
The problem is that my implementation is little more than a proof of concept and so it doesn't articulate the thesis very well. It doesn't scale, it is slow, it is unstable. The source is on http://github.com/anselm/imagewiki but ... basically it just isn't where I want it to be yet... and I am just too busy to bake a solution from scratch... Key Indexing for large numbers of dimensions sucks basically. And I'm looking for advice - actually ideally just something I can slap in and replace what I have. The current image recognition implementation is based on SIFT - from an off the shelf piece of code at the bottom of this page: http://en.wikipedia.org/wiki/Scale-invariant_feature_transform I'm thinking of switching to SURF ( and still need to research how it stores keys... ) but I think the keys may be smaller and more tractable there. At Where 2.0 I spoke to Blaise from Photosynth and he suggested talking to two people: David Nister ( http://www.vis.uky.edu/~dnister/ ) and Josef Sivec ( http://www.robots.ox.ac.uk/~josef/ ). Other people to talk to would be appreciated as well. If anybody has any simple practical advice that is low-energy on my part ( ideally off the shelf ) I'd like to swap out either our indexing system for our current SIFT keys or entirely replace the approach with a different kind of image matching technology. This would let this project actually work decently and I'd feel a lot better about talking about it and taking the whole idea further. Suggestions appreciated, - @anselm 415 215 4856 http://twitter.com/anselm _______________________________________________ Geowanking mailing list [email protected] http://geowanking.org/mailman/listinfo/geowanking_geowanking.org
