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ESP game
The ESP game (extrasensory perception game) is a human-based computation game developed to address the problem of creating difficult metadata. The idea behind the game is to use the computational power of humans to perform a task that computers cannot (originally, image recognition) by packaging the task as a game. It was originally conceived by Luis von Ahn of Carnegie Mellon University and first posted online in 2003.
At launch, the official website stated that "If the ESP game is played as much as other popular online games, we estimate that all the images on the Web can be labeled in a matter of weeks!" The original paper (2004) reported that a pair of players can produce 3.89 ± 0.69 labels per minute. At this rate, 5,000 people continuously playing the game would provide one label per image indexed by Google (425 million) in 31 days. 36 million labels were collected between the site's launch in October 2003 and May 2008.
In late 2008, the game was rebranded as GWAP ("game with a purpose"), with a new user interface. Some other games that were also created by Luis von Ahn, such as "Peekaboom" and "Phetch", were discontinued at that point. "Peekaboom" extends the ESP game by asking players to select the region of the image that corresponds to the label. "Squigl" asks players to trace the object outline in an image. "Matchin" asks players to pick the more beautiful out of two images. "Verbosity", which collects common-sense facts from players.
Google bought a license to create its own version of the game (Google Image Labeler) in 2006 in order to return better search results for its online images. The license of the data acquired by Ahn's ESP game, or the Google version, is not clear.[clarification needed] Google's version was shut down on September 16, 2011, as part of the Google Labs closure in September 2011.
Most of the ESP dataset is not publicly available. It was reported in the ImageNet paper that as of 2008, only 60K images and their labels can be accessed.
Image recognition was historically a task that was difficult for computers to perform independently. Humans are perfectly capable of it, but are not necessarily willing. By making the recognition task a "game", people are more likely to participate. When questioned about how much they enjoyed playing the game, collected data from users was extremely positive.
The applications and uses of having so many labeled images are significant; for example, more accurate image searching and accessibility for visually impaired users, by reading out an image's labels. Partnering two people to label images makes it more likely that entered words will be accurate. Since the only thing the two partners have in common is that they both see the same image, they must enter reasonable labels to have any chance of agreeing on one.
The ESP Game as it is currently implemented encourages players to assign "obvious" labels, which are most likely to lead to an agreement with the partner. But these labels can often be deduced from the labels already present using an appropriate language model and such labels therefore add only little information to the system. A Microsoft research project assigns probabilities to the next label to be added. This model is then used in a program, which plays the ESP game without looking at the image.
Hub AI
ESP game AI simulator
(@ESP game_simulator)
ESP game
The ESP game (extrasensory perception game) is a human-based computation game developed to address the problem of creating difficult metadata. The idea behind the game is to use the computational power of humans to perform a task that computers cannot (originally, image recognition) by packaging the task as a game. It was originally conceived by Luis von Ahn of Carnegie Mellon University and first posted online in 2003.
At launch, the official website stated that "If the ESP game is played as much as other popular online games, we estimate that all the images on the Web can be labeled in a matter of weeks!" The original paper (2004) reported that a pair of players can produce 3.89 ± 0.69 labels per minute. At this rate, 5,000 people continuously playing the game would provide one label per image indexed by Google (425 million) in 31 days. 36 million labels were collected between the site's launch in October 2003 and May 2008.
In late 2008, the game was rebranded as GWAP ("game with a purpose"), with a new user interface. Some other games that were also created by Luis von Ahn, such as "Peekaboom" and "Phetch", were discontinued at that point. "Peekaboom" extends the ESP game by asking players to select the region of the image that corresponds to the label. "Squigl" asks players to trace the object outline in an image. "Matchin" asks players to pick the more beautiful out of two images. "Verbosity", which collects common-sense facts from players.
Google bought a license to create its own version of the game (Google Image Labeler) in 2006 in order to return better search results for its online images. The license of the data acquired by Ahn's ESP game, or the Google version, is not clear.[clarification needed] Google's version was shut down on September 16, 2011, as part of the Google Labs closure in September 2011.
Most of the ESP dataset is not publicly available. It was reported in the ImageNet paper that as of 2008, only 60K images and their labels can be accessed.
Image recognition was historically a task that was difficult for computers to perform independently. Humans are perfectly capable of it, but are not necessarily willing. By making the recognition task a "game", people are more likely to participate. When questioned about how much they enjoyed playing the game, collected data from users was extremely positive.
The applications and uses of having so many labeled images are significant; for example, more accurate image searching and accessibility for visually impaired users, by reading out an image's labels. Partnering two people to label images makes it more likely that entered words will be accurate. Since the only thing the two partners have in common is that they both see the same image, they must enter reasonable labels to have any chance of agreeing on one.
The ESP Game as it is currently implemented encourages players to assign "obvious" labels, which are most likely to lead to an agreement with the partner. But these labels can often be deduced from the labels already present using an appropriate language model and such labels therefore add only little information to the system. A Microsoft research project assigns probabilities to the next label to be added. This model is then used in a program, which plays the ESP game without looking at the image.