Mobile picture guess: A crowdsourced serious game for simulating human perception

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Abstract

In this paper we present a novel idea that combines a mobile game with a Crowdsourcing campaign. The game is designed for studies into the visual saliency of image segments, where the game objective is for players to guess what is depicted in an image that is gradually uncovering. Game scores depend on the number of correct answers and the speed at which these are provided. With these game mechanics, we can determine the image segments that are most essential to players when asked to guess the image content, thereby assessing the most salient image regions. Through the combination of this game scenario and a Crowdsourcing campaign, we also present a way to tackle the rising demands for higher salaries in this line of work. By providing workers with an entertaining task, we aim to increase player motivation and hopefully make them want to play longer than required. In this paper we also present a sample study that evaluates the visual saliency of 200 animal images from Flickr. We conclude with preliminary results from the study and with our insights on how this approach can be applied to improve the current understanding of human visual perception.

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APA

Schicho, M., & Eg, R. (2015). Mobile picture guess: A crowdsourced serious game for simulating human perception. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8852, pp. 461–468). Springer Verlag. https://doi.org/10.1007/978-3-319-15168-7_56

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