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Crowdsourced object segmentation with a game Vincent Charvillat Amaia Salvador Aguilera Oge Marques Axel Carlier Xavier Gir i Nieto Outline Motivation Object Segmentation Experiments Results Conclusions Ongoing work

  1. Crowdsourced object segmentation with a game Vincent Charvillat Amaia Salvador Aguilera Oge Marques Axel Carlier Xavier Giró i Nieto

  2. Outline • Motivation • Object Segmentation • Experiments • Results • Conclusions • Ongoing work 2

  3. Motivation ? 3

  4. Motivation ? 4

  5. Semi-Supervised object segmentation Rough segmentation • B. C. Russell, A. Torralba, K. P. Murphy, and W. T. Freeman. Labelme: A database and web-based tool for image annotation. IJCV, 2008 5

  6. Semi-Supervised object segmentation • P. Arbelaez and L. Cohen. Constrained image segmentation from hierarchical boundaries. In CVPR'08, 2008. • 2) K. McGuinness and N. E. O'Connor. A comparative evaluation of interactive segmentation algorithms. 6

  7. Semi-Supervised object segmentation Boring task for users! 7

  8. 8

  9. Games with a purpose • J. Steggink and C. Snoek. Adding semantics to image-region annotations with the name-it- game. Multimedia Systems, 2011. • L. von Ahn, R. Liu, and M. Blum. Peekaboom: a game for locating objects in images. In CHI'06, 2006. 9

  10. Ask’nSeek A. Carlier, O. Marques, and V. Charvillat. Ask'nseek: A new game for object detection and labeling. In 10 ECCV'12 Workshops 2012.

  11. Motivation ? 11

  12. Outline • Motivation • Object Segmentation • Experiments • Results • Conclusions • Next steps 12

  13. Constrained parametric min-cuts for automatic object segmentation (CPMC) J. Carreira and C. Sminchisescu. Constrained parametric min-cuts for automatic object segmentation. In CVPR'10, 2010. 13

  14. Constrained parametric min-cuts for automatic object segmentation 14

  15. Motivation CPMC 15

  16. Outline • Motivation • Object Segmentation • Experiments • Results • Conclusions • Ongoing Work 16

  17. Experiments How many clicks do we need to achieve a certain quality in the segmentation? Test the algorithm for a large image dataset 17

  18. Pascal VOC2010 1928 images divided in: Train (964) Validation (964) 18

  19. Problem Simulator 19

  20. Simulator • The simulator generates points using the ground truth of the image. 20

  21. Simulator: Location of clicks S. Goferman, L. Zelnik-Manor, and A. Tal. Context-aware saliency detection. PAMI, 2012. 21

  22. Simulator: Foreground/Background ratio 22

  23. Outline • Motivation • Object Segmentation • Experiments • Results • Conclusions • Ongoing Work 23

  24. Jaccard index Measure of similarity between the segmentation result and the ground truth mask 24

  25. Results Using Pascal VOC2010 (Validation) 25

  26. Results Using Pascal VOC2010 (Validation) 26

  27. Outline • Motivation • Object Segmentation • Experiments • Results • Conclusions • Ongoing Work 27

  28. Conclusions • Realistic simulator to process large amounts of data. • Estimation of the expected AVERAGE Jaccard index by clicks. • Inter-class variance of results. 28

  29. Ongoing Work 29

  30. Ongoing Work • Image segmentation • CPMC candidates ● Label propagation through hierarchical partitions (eg. UCM, BPT…) ● Grabcut + Superpixels 30

  31. Ongoing Work • Data collection • Awarded with $250 in CrowdMM Competition (ACM MM Barcelona 2013). • Already more than 1500 games collected with 100 users More on that in our poster! 31

  32. Questions, suggestions… Thank you for your attention • Motivation • Object Segmentation • Experiments • Results • Conclusions • Ongoing Work 32

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