Happy Independence Day, America! I expect you’ll be busy making loud noises with explosives and generally partying it up this weekend, and I don’t begrudge you that*. But here’s some advice – if at some point you should decide to take a little drive somewhere to do something you maybe shouldn’t do, turn off the TomTom. [LOLnav based on an image by pizzodisevo]
You see, it turns out that not only does your satnav tell you how to get from A to B, it remembers where A and B were, when you travelled between them, and where you drove through on the way. Plus, if you’ve linked your phone to it via Bluetooth, it’ll have a record of every call and text message you made during the journey.
This isn’t a standard feature, obviously; it takes a detective with some good tech sk1llz0rz to tease out the old files, and now this has been revealed (by the superbly-monikered Beverly Nutter of London’s Metropolitan Police, no less) we can expect the same hacker enthusiasts who found the vulnerabilities to find a way of closing them.
So, just another front-line skirmish in the of the war between technology and privacy … but then if you’re doing nothing wrong, you have nothing to fear, right?
[ * Actually, I do kinda begrudge you it; the closest we Brits have to Independence Day is Guy Fawkes Night. I’ve always clung to the explanation for burning Fawkes in effigy that a slightly inebriated friend of my father’s told me when I was about twelve: “We’re not burning him for trying to blow up the government, Paul; we’re burning him because he failed.” Happy 4th July! ]
Finding photos in old books and not having any clue as to the locations they depict could become yet another mild annoyance thrown into the furnace of perpetual progress.
Comp-sci boffins at Carnegie-Mellon University have developed a system called IM2GPS that can identify the probable geographic location of a given image. From the abstract of the paper:
In this paper, we propose a simple algorithm for estimating a distribution over geographic locations from a single image using a purely data-driven scene matching approach. For this task, we will leverage a dataset of over 6 million GPS-tagged images from the Internet. We represent the estimated image location as a probability distribution over the Earth’s surface. We quantitatively evaluate our approach in several geolocation tasks and demonstrate encouraging performance (up to 30 times better than chance). We show that geolocation estimates can provide the basis for numerous other image understanding tasks such as population density estimation, land cover estimation or urban/rural classification.
The trend is towards every piece of data being tagged with a location: here we see a way of legacy information (old photos) being given a “probable geographic location” without having originally being created with a time/GPS location stamp. It would still only be a general guess as to a geographic area, but it is better than nothing.
This is part of a more general trend towards what Bruce Sterling calls Spimes. From the Man himself:
The most important thing to know about Spimes is that they are precisely located in space and time. They have histories. They are recorded, tracked, inventoried, and always associated with a story.
In the case of IM2GPS it is the data itself that is being recorded and tracked, and potentially the objects the data describes (the objects in the photos) which connects with another loosely related concept: the panopticon. Imagine if you combined IM2GPS technology with facial recognition software and put CCTV archives through this kind of process. You could essentially Spimify the population retrospectively!
Hysterically delusional paranoia aside this is a fascinating development. Read the paper in full (pdf), it’s well worth it.
[story via PhysOrg][images by Reto Stockli and QR-Code Generator]