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Click’n’Cut: Crowdsourced Interactive Segmentation with Object Candidates

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Carlier A, Salvador A, Giró-i-Nieto X, Marques O, Charvillat V. Click’n’Cut: Crowdsourced Interactive Segmentation with Object Candidates. In: 3rd International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). In Press


This paper introduces Click’n’Cut, a novel web tool for in- teractive object segmentation addressed to crowdsourcing tasks. Click’n’Cut combines bounding boxes and clicks gen- erated by workers to obtain accurate object segmentations. These segmentations are created by combining precomputed object candidates in a light computational fashion that al- lows an immediate response from the interface. Click’n’Cut has been tested with a crowdsourcing campaign to anno- tate a subset of the Berkeley Segmentation Dataset (BSDS). Results show competitive results with state of the art, es- pecially in time to converge to a high quality segmentation. The data collection campaign included golden standard tests to detect cheaters.




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