Tonchidot dissected
Really cool stuff. Cool stuff I’ve been wanting to do for a while now. Cool stuff we’re trying to do with Brightkite (minus the cool interface). Cool stuff I didn’t think was technologically feasible on today’s devices yet. Did they figure it out somehow?
Since they gave out very little information, here’s what I think would be necessary, technology-wise, to make this happen, and also why I think that this demo wasn’t real.
Fairly accurate location of the device…less than a meter
If this was based on image recognition alone, it would be extremely difficult…there are just too many places in the world, and things look different when viewed from different angles, under different lighting conditions, etc. Furthermore, “Anshin does say that no image-recognition technology is being used”. So, location is key.
To get anywhere close to the location accuracy that they need to pull this off, they either need GPS or Wi-fi triangulation, and even then, I am not sure whether it would be accurate enough for some of the extreme cases (close-ups of phones on a shelf). Now, it seems that most of their stuff was demoed inside a mall. GPS works really poorly indoors, so I am fairly certain that they wouldn’t get an accurate enough location fix using that. Wi-Fi triangulation can get this accurate, but has really poor coverage…if that’s what they are using, expect this stuff to work well in very, very few places.
Good sense of direction, or viewing angle
Here, the accelerometer seems the obvious technology that’s being used. I’m not sure how accurate the results are, but I think this is feasible using a stock iPhone, once properly calibrated. Google showed off something similar on Android with their Street View demo.
Depth of field, or distance to object
In order to prevent stuff that is behind walls, etc. to show up, you’d need an idea of the depth of field, i.e. how far are you looking, and how far object are away from your position.
Usually, this sort of stuff is done using special sensors (most digital cameras have them), or using a laser rangefinder. Obviously, they iPhone has neither.
I believe that some of that can be done using image analysis (fellow Techstars team Occipital showed some really cool stuff a couple of weeks ago). No idea if it can be done with just one photo from one angle, but I’ll give them that one.
Crazy-fast connection…things were popping up really fast…or really good caching
In the demo, things were super-fluid…which either means they are loading data really fast of their servers (doubtful with the iPhone’s connectivity), or the stuff was cached. I’m assuming the latter, which wouldn’t be too difficult if you don’t have too much data in one spot. If you do, good luck :)
If all of those things were solved, there of course remain the obvious challenges of what happens when stuff moves, etc, but I’ll just leave those be for now because I think that the app can be cool without solving that problem.
All that being said, I really doubt that their demo was real. It is entirely possible to get an approximation of something like Tonchidot to function on an iPhone today (in fact, we are working on some stuff like that), BUT not at the accuracy that they were showing. I just don’t see any way, short of crazy image recognition (which they said they don’t use), to make this work with an iPhone. The demo is of course incredibly cool, and I really hope that I’m wrong and that we see their app in the store in the coming months, but I am extremely sceptical. If it does come out, I predict that it won’t work as shown in the demo.
I’d love to hear your thoughts and comments.



