1. CrowdSearch: Exploiting Crowds for Accurate Real-time Image Search on Mobile Phones Original work by Yan, Kumar & Ganesan Presented by Shibo Li & Jian Yu

2. Problem Definition How to search information? 2

3. Problem Definition Mobile-based search will become more important in the future. – More than 70% of smart phone users perform searches. Expected to be more mobile searches than non-mobile searches soon – Text-based mobile searches are easy as well… What about searching images? 3

4. Problem Definition Image search using mobile phones 4

5. Problem Definition Automatic searching 5

6. Idea Image searching based on crowd source. 6 CrowdSearch Algorithm

7. Challenges Automatic image search: – Delay↓, Cost ↓, Accuracy ↓ People validation image search: – Delay ↑, Cost ↑, Accuracy ↑ 7

8. CrowdSearch Algorithm OverviewImplementation & EvaluationsThroughts & Criticisms 8

9. CrowdSearch: Overview 9

10. 10

11. CrowdSearch: Overview 11

12. CrowdSearch: Overview 12

13. CrowdSearch: Overview 13

14. Challenge: Accuracy 14

15. Challenge: Accuracy Human validation improves accuracy 2-5 times. Majority(5) can achieve the highest accuracy up to 95% So we send each image to 5 people to get the majority feedback. 15

16. Challenge: Delay & Cost tradeoff 16

17. Challenge: Delay & Cost tradeoff Parallel Scheme 17

18. Challenge: Delay & Cost tradeoff Serial Scheme 18

19. CrowdSearch: compromised scheme 19

20. CrowdSearch: compromised scheme Prediction requires delay and accuracy models 20

21. Delay Model 21 Statistically, both of the delays follow the exponential distribution. Overall delay distribution is the convolution of the acceptance and submission delay.

22. Delay Prediction 22

23. Accuracy Prediction 23

24. Decision Engine 24

25. OverviewImplementation & EvaluationsThroughts & Criticisms 25

26. Implementation 26

27. Power Consideration Should some image processing occur on the local device or should it be outsourced to the server? – Use remote processing when WiFi is available. – Use local processing when only 3G is available 27

28. Evaluation Delay model meets the exponential distribution 28

29. CrowdSearch Performance CrowdSearch optimized algorithm 29

30. OverviewImplementation & EvaluationsThroughts & Criticisms 30

31. Thoughts/Criticism Only 1000 images in the backend database. – Would increasing the number of automated search images increase total task time in a significant way? The evaluation only based on 4 categories. – Buildings, Books, Flowers and Faces Suggestion: Internet database Let the user to choose the categories Too many distractions in a single image 31

32. Thoughts/Criticism Too many disturbances in a single image 32

33. Q&A Thank you! 33