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Lecture 26: Vision for the Internet CS6670: Computer Vision Noah Snavely.

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Presentation on theme: "Lecture 26: Vision for the Internet CS6670: Computer Vision Noah Snavely."— Presentation transcript:

1 Lecture 26: Vision for the Internet CS6670: Computer Vision Noah Snavely

2 Announcements Wednesday’s class cancelled Final project status reports due Wednesday Office hours this week: Tuesday 9:30 – 11am

3 Vision and the Internet

4 How is the Internet useful for Computer Vision? 1.As a source of data 2.As a source of people with too much free time

5 How is the Internet useful for Computer Vision? 3.As a source of new applications

6 The Internet as source of labor Next slides courtesy Luis von Ahn

7 Mechanical Turk

8

9 Mechanical Turk – Demographics United States76.25% India8.03% United Kingdom3.34% Canada 2.34% Age distribution Motivation

10 LABELING IMAGES WITH WORDS MARTHA STEWART FLOWERS SUPER EVIL STILL AN OPEN PROBLEM Slides courtesy Luis von Ahn

11 IMAGE SEARCH ON THE WEB USES FILENAMES AND HTML TEXT

12 TWO-PLAYER ONLINE GAME PARTNERS DON’T KNOW EACH OTHER AND CAN’T COMMUNICATE OBJECT OF THE GAME: TYPE THE SAME WORD THE ONLY THING IN COMMON IS AN IMAGE THE ESP GAME

13 PLAYER 1PLAYER 2 GUESSING: CARGUESSING: BOY GUESSING: CAR SUCCESS! YOU AGREE ON CAR SUCCESS! YOU AGREE ON CAR GUESSING: KID GUESSING: HAT THE ESP GAME

14 © 2004 Carnegie Mellon University, all rights reserved. Patent Pending.

15 4.1 MILLION LABELS WITH 23,000 PLAYERS THE ESP GAME IS FUN THERE ARE MANY PEOPLE THAT PLAY OVER 20 HOURS A WEEK

16 SAMPLE LABELS BEACH CHAIRS SEA PEOPLE MAN WOMAN PLANT OCEAN TALKING WATER PORCH

17 REVEALING IMAGES REVEALERGUESSER CAR PARTNER’S GUESS BRUSH BRUSH CAR CAR

18 How can we choose a set of representative images? Statistics over large numbers of people Flickr results: “Pantheon”

19 How can we choose representative images?

20 Scene summarization [Simon, Snavely, Seitz, ICCV 2007]

21 Scene summarization – tags

22 Typical Flickr tags

23 Scene segmentation [Simon and Seitz, ECCV 2008]

24 Scene exploration

25 Mapping the World’s Photos [Crandall, Backstrom, Huttenlocher, Kleinberg, WWW ‘09]

26 Mapping the World’s Photos [Crandall, Backstrom, Huttenlocher, Kleinberg, WWW ‘09]

27 The Internet as a source of applications

28

29 Using social networks for recognition [Stone, Zickler, and Darrell, Workshop on Internet Vision 2008]

30 Using social networks for recognition Useful information: Which pairs of people are friends? Who are the photographer’s friends? Which people have appeared together in the past? Who appears most often in the photographer’s photos? [Stone, Zickler, and Darrell, Workshop on Internet Vision 2008]

31 Using social networks for recognition [Stone, Zickler, and Darrell, Workshop on Internet Vision 2008]

32 Camera calibration "Priors for Large Photo Collections and What They Reveal about Cameras," S. Kuthirummal, A. Agarwala, D. B Goldman, and S. K. Nayar, European Conference on Computer Vision, 2010

33 Questions? See you on Tuesday, May. 17, 2 – 4:30! Look for email regarding signup times


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