Month: October 2008

I finally got a chance to try out SnapTell Explorer, and I have to say that I’m impressed. Almost all of books and CDs I had lying around were correctly recognised, despite being pretty obscure titles. With 2.5 million objects in their index, SnapTell can recognise just about any book, CD, DVD or game. Once the title is recognised, you get back a result page like this with a brief review and the option to buy it on Amazon, or search Google, Yahoo or Wikipedia. For music, there is a link to iTunes.

I spent a while “teasing”  the search engine with badly taken photos, and the recognition is very robust. It has no problems with blur, rotation, oblique views, background clutter or partial occlusion of the object. Below is a real recognition example:

I did find the service pretty slow, despite having a WiFi connection. Searches took about five seconds.  I had a similar experience with kooaba earlier.  There are published visual search algorithms that would let these services be as responsive as Google, so I do wonder what’s going on here. It’s possible the speed issue is somewhere else in the process, or possibly they’re using brute-force descriptor comparison to ensure high recognition rate. For a compelling experience, they desperately need to be faster.

While the recognition rate was generally excellent, I did manage to generate a few incorrect matches. One failure mode is where multiple titles have similar cover design (think “X for Dummies”)  – a picture of one title randomly returns one of the others. I saw a similar problem with a CD mismatching to another title because both featured the same record company logo. Another failure mode that might be more surprising to people who haven’t worked with these systems was mismatching on font. A few book searches returned completely unrelated titles which happened to use the same font on the cover. This happened particularly when the query image had a very plain cover, so there was no other texture to disambiguate it. The reason this can happen is that the search method relies on local shape information around sets of interest points, rather than attempt to recognise the book title as a whole by OCR.

My overall impression, however, is that this technology is very much ready for prime time. It’s easy to see visual search becoming the easiest and fastest way to get information about anything around you.

If you haven’t got an iPhone, you can try it by sending a picture to [email protected].

Well well. Hot on the heals of kooaba, competitor SnapTell just released an iPhone client for their visual search engine. A little sleuthing reveals that the index contains 2.5 million items – apparently most books, DVDs, CDs and game covers.  If the recognition rate is as high as it should be, that’s a pretty impressive achievement. In principle the service was already available via email/mms. In practice, an iPhone client changes the experience completely. Image search becomes the fastest way to get information about anything around you.

I really think this technology is going to take off big-time in the near future.  The marketing intelligentsia are aware of this too. There is an adoption challenge, but SnapTell in particular are already running an excellent high profile education/promotion campaign with print magazines. They’re not messing about either: The campaign is running in Rolling Stone, GQ, Men’s Health, ESPN, Wired and Martha Stewart Weddings. In short, publications that reach a substantial chunk of the reading public. Whether the message will carry over that the technology is good for more than signing up for free deoderant samples is something I’m a little skeptical about, but in the short term it’s a ready revenue stream for the startup, and a serious quantity of collateral publicity.

Usage report later when I can get hold of an iPhone.

Update: I just got to try it, and it’s really rather good. First impressions here.