Google has launched a clone of the ESP Game with the rather dull name Google Image Labeler.
Google Image Labeler is a simple game where two anonymous, random people try to agree on labels for images. The idea here is to get people to do useful work, such as providing accurate labels for images, by trying to make it into a fun game.
See also my earlier post, "Human computation and playing games", where I talk about ESP Game and Luis von Ahn's other work in more detail.
See also Luis von Ahn's talk at Google on Google Video, "Human Computation". It is a light, fun, and very interesting talk that includes demos of these types of games and the value of the data derived from the games.
[Found via Philipp Lenssen]
Update: Danny Sullivan reports that Google licensed the ESP Game from Luis von Ahn.
Update: A Google engEDU talk on Google Video, "Using Statistics to Search and Annotate Pictures", by UCSD Professor Nuno Vasconcelos gives some nice examples of how this kind of image labeling data can be useful for image search.
Update: A couple other talks are worth considering here as well. First, a talk "Detecting and Recognizing Objects In Natural Images" might be another in a long line of applying probabilistic models to finding objects in images, but I particularly enjoyed the demo at 15:00 of their text recognition in that talk. Second, I thought "Automated Reconstruction of 3D Models" had some impressive ideas about how to quickly get detailed 3D city models into mapping software like Google Maps and Google Earth.
Subscribe to:
Post Comments (Atom)
6 comments:
I've been surprised at how few people recognized or found the connection to The ESP Game. Glad to see someone reporting on it from that angle.
You're right, that talk was really excellent. I'm looking forward to seeing what else he does.
I'm also a little surprised. The ESP Game is really fun. Google's version is surprisingly dull, and it's not just the title. ;) I wonder why they didn't do more with it?!
At least this means the Google Image Search will be improved. This also could be seen as a rather big step for Google, who believe in having algorithms and computers do all the work...
Greg,
I would love to hear your thoughts on this: Considering google licensed the game from Ahn, everyone seems to credit google for pioneering this kinda effort.
I think amazon's "Mechanical Turk" got it first truly with their more generic version, where "image labeling" is just one scenario among many, in getting the masses take part in this kind of "reverse Turing" tests, or as amazon calls it "HIT"s. (Yes, the big flaw in AMT is the walled "paid model" that restricts the participants; Luis does mock amazon's paid model in the video)
For that matter, yahoo has been doing this for a while as well...using Flickr's user-generated tags in search results. Bradley Horowitz called it "Better Search Through People", in one of his blogs.
Ex-Amazonian, I think it is an interesting direction, but you do have to expect people to cheat, vandalize, and spam. In these systems, features to increase data quality and hinder spam should be designed in early.
Luis von Ahn did this in all of his work. MTurk and most tagging systems do not appear to have been as careful.
Google congratulates von Ahn for receiving a Macarthur fellowship.
In the past couple of weeks, I've been turning to image labeler for 5 to 10 minutes when my brain needs a break from work. It seems to me (at this point in 2007) that people have indeed figured out how to "cheat" the image labeler and end up with outrageously high scores. For example, today all the top 10 scores have names like "plzstopcheating". The leader board and game mentality must be encouraging this (the cheating, not those names). I went off on a web search to see if I could figure out how they are doing it, but so far, nothing! (just comments like this that it would be hard to cheat.)
most likely 2 people decide to use one word such as "the" and only type that. once they find a partner who keeps doing the same then they know they've found each other. simple really lol
Post a Comment