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Google Image labeler: google's way of indexing images' content


Google Image Labeler is a new feature of Google Image Search that allows you to label random images and help improve the quality of Google's image search results.

Each user who wants to participate will be paired randomly with a partner who's currently online and also using Google Image Labeler. Over a 90-second period, both participants will be shown the same set of images and asked to label each image based on what they see. They'll also be shown words that can't be used as labels. Both participants can add as many labels as they want until one of them matches a partner's label. After there's a match, they'll see a new image and continue the cycle, until time runs out. Contributors will also see points they've earned throughout the session.-
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Now isn't that smart?
Google has transformed a tedious (and payed) job into a game for the masses. Although there are points involved, there's no prize or anything:
What are these points for? Can I redeem them for anything?

They're intended to help identify contributions from participants. But they're not redeemable.
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Here's a v interesting google video on Human Computation (don't know if it's the actual forerunner of image labelling):

Luis von Ahn is an assistant professor in the Computer Science Department at Carnegie Mellon University,  ... all ยป where he also received his Ph.D. in 2005. Previously, Luis obtained a B.S. in mathematics from Duke University in 2000. He is the recipient of a Microsoft Research Fellowship.

ABSTRACT Tasks like image recognition are trivial for humans, but continue to challenge even the most sophisticated computer programs. This talk introduces a paradigm for utilizing human processing power to solve problems that computers cannot yet solve. Traditional approaches to solving such problems focus on improving software. I advocate a novel approach: constructively channel human brainpower using computer games. For example, the ESP Game, described in this talk, is an enjoyable online game -- many people play over 40 hours a week -- and when people play, they help label images on the Web with descriptive keywords. These keywords can be used to significantly improve the accuracy of image search. People play the game not because they want to help, but because they enjoy it.

I describe other examples of "games with a purpose": Peekaboom, which helps determine the location of objects in images, and Verbosity, which collects common-sense knowledge. I also explain a general approach for constructing games with a purpose.
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How was Google Image Labeler developed?

Google Image Labeler is based in part on technology licensed from and developed at Carnegie Mellon University.-
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Yep, you got it right :)

can't wait for the same business model to be tried in running sweatshops.

nah, it's not slave labour - they're all just playing a game. financial reward would ruin their enjoyment.


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