C. Bryan, A. Russell, . Torralba, P. Kevin, . Murphy et al., Labelme: a database and web-based tool for image annotation, International journal of computer vision, vol.77, issue.1-3, pp.157-173, 2008.

T. Lin, M. Maire, S. Belongie, J. Hays, P. Perona et al., Microsoft COCO: Common Objects in Context, 2014.
DOI : 10.1007/978-3-319-10602-1_48

A. Carlier, V. Charvillat, A. Salvador, X. G. Nieto, and O. Marques, Click'n'Cut, Proceedings of the 2014 International ACM Workshop on Crowdsourcing for Multimedia, CrowdMM '14, pp.53-56, 2014.
DOI : 10.1145/2660114.2660125

A. Salvador, A. Carlier, X. Giro-i-nieto, O. Marques, and V. Charvillat, Crowdsourced object segmentation with a game, Proceedings of the 2nd ACM international workshop on Crowdsourcing for multimedia, CrowdMM '13, pp.15-20, 2013.
DOI : 10.1145/2506364.2506367

P. Arbeláez and L. Cohen, Constrained image segmentation from hierarchical boundaries, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587492

C. Rother, V. Kolmogorov, and A. Blake, "GrabCut", ACM Transactions on Graphics, vol.23, issue.3, pp.309-314, 2004.
DOI : 10.1145/1015706.1015720

K. Mcguinness and N. E. Connor, A comparative evaluation of interactive segmentation algorithms, Pattern Recognition, vol.43, issue.2, 2010.
DOI : 10.1016/j.patcog.2009.03.008

X. Nieto, Neus Camps, and Ferran Marques Gat: a graphical annotation tool for semantic regions, Multimedia Tools and Applications, pp.155-174, 2010.

D. Oleson, A. Sorokin, P. Greg, V. Laughlin, J. Hester et al., Programmatic gold: Targeted and scalable quality assurance in crowdsourcing Human computation, 2011.

L. Gottlieb, J. Choi, P. Kelm, T. Sikora, and G. Friedland, Pushing the limits of mechanical turk, Proceedings of the ACM multimedia 2012 workshop on Crowdsourcing for multimedia, CrowdMM '12, pp.23-28, 2012.
DOI : 10.1145/2390803.2390815

H. Su, J. Deng, and L. Fei-fei, Crowdsourcing annotations for visual object detection, Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012.

L. Von-ahn and L. Dabbish, Designing games with a purpose, Communications of the ACM, vol.51, issue.8, pp.58-67, 2008.
DOI : 10.1145/1378704.1378719

A. Mao, E. Kamar, Y. Chen, E. Horvitz, E. Megan et al., Volunteering versus work for pay: Incentives and tradeoffs in crowdsourcing, First AAAI Conference on Human Computation and Crowdsourcing, 2013.

G. Panagiotis, F. Ipeirotis, J. Provost, and . Wang, Quality management on amazon mechanical turk, Proceedings of the ACM SIGKDD workshop on human computation, pp.64-67, 2010.

P. Welinder and P. Perona, Online crowdsourcing: Rating annotators and obtaining cost-effective labels, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Workshops, pp.25-32, 2010.
DOI : 10.1109/CVPRW.2010.5543189

URL : http://authors.library.caltech.edu/47669/1/WelinderPerona10.pdf

J. Whitehill, . Ting-fan, J. Wu, J. R. Bergsma, . Movellan et al., Whose vote should count more: Optimal integration of labels from labelers of unknown expertise, Advances in neural information processing systems, pp.2035-2043, 2009.

S. Vijayanarasimhan and K. Grauman, Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds, International Journal of Computer Vision, vol.36, issue.2, pp.97-114, 2014.
DOI : 10.1007/s11263-014-0721-9

D. Martin, C. Fowlkes, D. Tal, and J. Malik, A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.416-423, 2001.
DOI : 10.1109/ICCV.2001.937655

M. Everingham, L. Van-gool, C. K. Williams, J. Winn, and A. Zisserman, The Pascal Visual Object Classes (VOC) Challenge, International Journal of Computer Vision, vol.73, issue.2, 2010.
DOI : 10.1007/s11263-009-0275-4

P. Arbelaez, J. Pont-tuset, J. Barron, F. Marques, and J. Malik, Multiscale Combinatorial Grouping, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.328-335, 2014.
DOI : 10.1109/CVPR.2014.49

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.433.2307

R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua et al., Slic superpixels compared to state-of-the-art superpixel methods Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.34, issue.11, pp.2274-2282, 2012.

P. Felzenszwalb and D. Huttenlocher, Efficient Graph-Based Image Segmentation, International Journal of Computer Vision, vol.59, issue.2, pp.167-181, 2004.
DOI : 10.1023/B:VISI.0000022288.19776.77