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Computer Scientists Scour Your Holiday Photos

Barence writes "Hundreds of thousands of images on Flickr are being used to teach a program to determine the geographic location of an image, simply by looking at it. The program attempts to mimic the way that humans can deduce the location of an image by searching for visual clues, such as similarities to pictures or locations they have seen previously. In its current state it can guess the location of a photo to within 200km, 16% of the time — extremely accurate given the complexity of the problem."

23 of 156 comments (clear)

  1. Where pictures are taken by tomalpha · · Score: 5, Informative

    The paper referenced in the article has an interesting density map of where their 20 million source photos were taken (ok, so they only ended up using 200 or so of these). It says it uses a logarithmic scale, and seems to imply that the vast majority of photos available to them on Flickr were taken in one of only a handful of locations:

    • London
    • Paris
    • New York
    • Washington
    • Los Angeles
    • Tokyo

    Ok so there are a couple more than this, and my geography is appalling, but these seem to be the only areas that are are coloured red.

    1. Re:Where pictures are taken by elguillelmo · · Score: 5, Interesting

      then... if there are 6 sources of pictures, by blindfold guessing you'll get it right 16.66..% of the time

      --
      Dawkins Revisited: A person is shit's way of making more shit -- Steve Barnett, anthropologist.
    2. Re:Where pictures are taken by SteveAyre · · Score: 4, Funny

      So it's actually less accurate than if it just guessed? :)

    3. Re:Where pictures are taken by Melfina · · Score: 4, Funny

      It's like answering 'True' in a multiple choice test!

      --
      :3 rawr.
    4. Re:Where pictures are taken by raehl · · Score: 4, Insightful

      Actually, the earth is pretty big - you'd have only a 0.0246% of being within 200km of someone, counting water. Get rid of water and you get to around 0.075%.

    5. Re:Where pictures are taken by 1729 · · Score: 4, Insightful

      That's if you choose points at random. If you only choose points corresponding to cities with large populations that frequently use internet photo-sharing sites, then your chances of being within 200km of the location become much better.

  2. Dude where's my photo by stainlesssteelpat · · Score: 5, Funny

    Dude, that's as accurate as my girlfriends map navigation. *sigh*

    --
    War is the statesman's game, the priest's delight, the lawyer's jest, the hired assassin's trade.- Shelley
  3. heh by Kingrames · · Score: 4, Funny

    Show it a picture of the andromeda galaxy and throw its statistics way off.

    --
    If you can read this, I forgot to post anonymously.
    1. Re:heh by somersault · · Score: 4, Funny

      Nopes - it will guess "Starbucks", and there's always one within 200km, even in Andromeda.

      --
      which is totally what she said
  4. Obligatory - I can get it within 6378km 100% by SlashTon · · Score: 5, Funny

    of the time...

    (Not counting those rich bastards who can afford taking a holiday on the ISS).

  5. Automatic Carmen San diego by goombah99 · · Score: 4, Funny

    Where's Goatse?

    --
    Some drink at the fountain of knowledge. Others just gargle.
    1. Re:Automatic Carmen San diego by Anonymous Coward · · Score: 5, Funny

      Where's Goatse? Uranus?
  6. Statistics is important by UnknowingFool · · Score: 4, Funny
    Just like all statistics getting a good sample population is very important. If this program were to sample the /. population, it would come to one of two conclusions.
    1. We have no holidays as we don't socialize.
    2. We all live within 1.0 km of a basement. :P
    --
    Well, there's spam egg sausage and spam, that's not got much spam in it.
  7. Photosynth looks cooler by Bombula · · Score: 4, Informative
    The Photosynth multi-resolution and image-recognition tech demonstrated at TED looked cooler if you ask me:

    metacafe link here and TED link here.

    --
    A-Bomb
  8. Scientist make new discovery by Anonymous Coward · · Score: 4, Funny
    Machine is shown hundreds of thousands of holiday pictures from Flickr.



    Scientists surprised to discover it is possible for a machine to loose will to live.

  9. Source code by RandoX · · Score: 4, Funny

    It's a for loop that spits out "Your mom's basement".

  10. This is very hard by mzs · · Score: 4, Insightful

    Look at this set of pictures:

    http://htmlhelp.com/~liam/Hawaii/Kauai/WaimeaCanyon/

    Would you know simply by looking at the photos without the sign that this was not say the grand canyon? The whole correct to 200 km aspect is troublesome when the state of the art in computer vision cannot yet even answer that this is a picture of a canyon.

  11. Just checked on flickr... by stoofa · · Score: 4, Funny

    OsamaBinLaden2001 has deleted his account

  12. Missing double blind by RichMan · · Score: 4, Insightful

    From the looks of the test selecting London all the time would have a
    1/6 chance = 16.67% chance.

    They need better double blind testing and a more diverse set of geographical locations.

  13. Re:Random pick is correct ~8% of the time by Anonymous Coward · · Score: 4, Informative

    Re-check your math that is wrong.
    Should be .08%

  14. Moon Landing pictures! by erroneus · · Score: 4, Funny

    I'd like to present this with Moon landing pictures to see where the moon landing was staged! (hahaha... love it)

  15. Actually, he kinda understands.... by raehl · · Score: 4, Insightful

    The dice analogy is right-on.

    The problem is he just doesn't seem to realize that the chances of throwing doubles are 16.66%.

  16. Automatic image recognition is no walk in the park by hedu · · Score: 4, Interesting

    Reminds me of the experiment done in a Dutch military lab a couple of years ago. They trained a neural network to recognize whether a photograph taken out on a country road had a military vehicle in it or not.

    The system recognized the photos from the training set perfectly, but did no better than random on images fed to it that were taken at different times.

    Turns out all the training shots with a military vehicle in it had been taken on a sunny day, and the control shots without one had been taken when it was overcast. The system had been trained to recognize a different thing from what they intended!