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Opinion
Augmenting Reality: Measuring It First
5/31/2007
My son makes a "fortune" delivering pizzas in Ann Arbor. Seriously, he saves enough money during the school year that he can afford to take summers off, like school teachers, except in his case he's honing his Frisbee golf skills. Last summer he traveled 12,000 miles and visited 240 courses.That was also the summer he learned to do more things on his Treo 650 than I know how to do on mine. It's really annoying how fast he can check the weather, get a map or directions, and locate the nearest Subway store. The coolest thing about what he's doing with his handheld device, though, is that even though he is--for the moment--a bit geekish for doing so, it's clear that other young consumers are going to want to do what he does.
That means that the folks at Apple and Google and all the startups in between are going to be making it easy for other consumers to do even niftier things. They're aiming, of course, at young people, but that means they'll make it easy enough for me, too. The only thing they won't do that I wish they would is make all of this stuff readable for me without my reading glasses.
A glimpse ahead into the future of what handhelds might be able to do is provided in a recent article, TR10: Augmented Reality, in MIT's Technology Review magazine. A research team from Finland:
... Added a GPS sensor, a compass, and accelerometers to a Nokia smart phone. Using data from these sensors, the phone can calculate the location of just about any object its camera is aimed at. Each time the phone changes location, it retrieves the names and geographical coördinates of nearby landmarks from an external database. The user can then download additional information about a chosen location from the Web--say, the names of businesses in the Empire State Building, the cost of visiting the building's observatories, or hours and menus for its five eateries.Another company, from France, is working on doing similar things using picture analysis:
Relying on software alone, Total Immersion's system begins with a single still image of whatever object the camera is aimed at, plus a rough digital model of that object; image-recognition algorithms then determine what data should be superimposed on the image.
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