Crowdsourced object segmentation with a game

Authors:
Amaia Salvador;Axel Carlier;Xavier Giro-i-Nieto;Oge Marques;Vincent Charvillat
Affiliations:
IRIT-ENSEEIHT, University of Toulouse, Toulouse, France;IRIT-ENSEEIHT, University of Toulouse, Toulouse, France;Universitat Politecnica de Catalunya, Barcelona, Spain;Florida Atlantic University, Boca Raton, USA;IRIT-ENSEEIHT, University of Toulouse, Toulouse, France
Venue:
Proceedings of the 2nd ACM international workshop on Crowdsourcing for multimedia
Year:
2013

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Abstract

We introduce a new algorithm for image segmentation based on crowdsourcing through a game : Ask'nSeek. The game provides information on the objects of an image, under the form of clicks that are either on the object, or on the back-ground. These logs are then used in order to determine the best segmentation for an object among a set of candidates generated by the state-of-the-art CPMC algorithm. We also introduce a simulator that allows the generation of game logs and therefore gives insight about the number of games needed on an image to perform acceptable segmentation.