Today kooaba released their iPhone client. It’s a visual search engine – you take a picture of something, and get search results. The YouTube clip below shows it in action. Since this is the kind of thing I work on all day long, I’ve got a strong professional interest. Haven’t had a chance to actually try it yet, but I’ll post an update once I can nab a friend with an iPhone this afternoon to give it a test run.
At the moment it only recognises movie posters. Basically it’s current form is more of a technology demo than something really useful. Plans are to expand to recognise other things like books, DVDs, etc. I think there’s huge potential for this stuff. Snap a movie poster, see the trailer or get the soundtrack. Snap a book cover, see the reviews on Amazon. Snap an ad in a magazine, buy the product. Snap a resturant, get reviews. Most of the real world becomes clickable. Everything is a link.
The technology is very scalable – The internals use an inverted index just like normal text search engines. In my own research I’m working with hundreds of thousands of images right now. It’s probably going to be possible to index a sizeable fraction of all the objects in the world – literally take a picture of anything and get search results. The technology is certainly fast enough, though how the recognition rate will hold up with such large databases is currently unknown.
My only question is – where’s the buzz, and why has it taken them so long?
Update: I gave the app a spin today on a friend’s iPhone, and it basically works as advertised. It was rather slow though – maybe 5 seconds per search. I’m not sure if this was a network issue (though the iPhone had a WiFi connection), or maybe kooaba got more traffic today than they were expecting. The core algorithm is fast – easily less than 0.2 seconds (and even faster with the latest GPU-based feature detection). I am sure the speed issue will be fixed soon. Recognition seemed fine, my friend’s first choice of movie was located no problem. A little internet sleuthing shows that they currently have 5363 movie posters in their database. Recognition shouldn’t be an issue until the database gets much larger.
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