Peekaboom: A Game for Locating Objects in Images

Roy Liu

Carnegie Mellon University

Joint work with Luis von Ahn and Manuel Blum

Object Location in Images

Given an image, determine what objects there are and locate them:

Woman

Man

Umbrella

Tree

Sailboat

Dog

As Things Stand Now

No algorithm is known for taking an image and determining what objects are in it, let alone telling you where they are.

Fortunately, this talk isn’t about developing such an algorithm. Let’s try a different approach.

Harnessing the Power of Human Cycles

“Math is hard. Let’s go shopping!” –BarbieOn similar line of thinking:

• Programming computers to locate objects in images is hard, so…

• Let’s not think about it.• Instead, let’s get humans to do the work for

us.

Problems

Wait! Your average human probably wants:

• Enjoyment – they want to have a good time• Incentives – they want something in return

How do we address both?

A Game

Have people do the work for us by playing a game.

Many design issues arise:• What will be the core idea of the game?• How do we collect data?• How do we ensure the quality of the data?

An Earlier Idea: Luis von Ahn’s ESP Game

Two players, with no communication, each try to guess what the other is thinking about a particular image they both see.

If they agree on a word, the game moves on and increases both players’ scores.

A Sample Run

Player 2 Guesses

• Woman• Shirt• Denim• Girl• Model

Player 1 Guesses

• Pants• Model• Lady

Server: Agreed, “Model”

Why ESP Works

By agreeing on a word, the players:• Say what it is – we call this assigning a “label”

to the image.• Check their own work – the fact that two

strangers agree on a label is a witness of the label’s quality.

The Limitations of ESP

The ESP Game can label images (and consequently tell you what’s in them), but it cannot:• Find the objects being labeled.• Determine the way in which the object

appears – does the label “car” refer to the text “car” or an actual car in the image?

Completing the Image Cycle

unlabeled images ESP game serverlabeled images

located images Peekaboom game server

A New Idea: Peekaboom

Two players are assigned the roles of “revealer” and “guesser”.

The revealer sees an image with a label. The guesser sees nothing.

The revealer shows the guesser parts of the image. If the guesser guesses correctly, the game moves on.

Statement of Purpose

We would like to collect data about images systematically and en masse.

We hope our collection will form the basis for data sets that can be used to train computer vision algorithms.

A (Simplified) Trial Run

The Revealer clicks on parts of the image and shows them to the Guesser.

The Guesser guesses:•Flower•Petal•Butterfly

Server: Correct, Butterfly

Why Peekaboom Works

By getting the guesser to guess correctly, the revealer locates objects by clicking on the relevant parts of the image:

But Wait, There’s More

Peekaboom not only locates objects, but also:• Gives the context necessary to identify them.• Classifies the image as “Text”, “Noun”, or

“Verb” by way of hints.Let’s examine how Peekaboom does both.

•Pings help separate the context of object with the object itself.•They help the guesser distinguish trunk from other possibly correct labels like “elephant”, “tusk”, and “ear”.

The label: trunk

Object Context

Hints

The label “car” is ambiguous --

this is “car”

this is also “car”

The hints help distinguish the manner in which the label “car” appears:

this is the object “car”

this is the text “car”

The Architecture of Peekaboom

game server

players

compiler

researchers

players

labeled images

located images

raw data

Peekaboom is…

funnovelaesthetically appealingnetworkedscalablewidely deployable

Conclusions

Peekaboom will be released to a general audience within two months.

We hope that it will solve difficult AI tasks while achieving:• Low costs – One game server.• Quality – Accurately locate objects in images.• Quantity – Locate objects in millions of

images.

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The best way to understand this talk is to try the game out for yourself:

www.peekaboom.org

We look forward to collecting your cycles!