Crowdsourced object segmentation with a game
Amaia Salvador, Axel Carlier, Xavier Giró-i-Nieto, Oge Marques, Vincent Charvillat · 2013
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.