Finding Image Regions with Human Computation and Games with a Purpose

M. Lux, Mario Guggenberger
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Abstract

Manual image annotation is a tedious and time-consuming task, while automated methods are error prone and limited in their results. Human computation, and especially games with a purpose, have shown potential to create high quality annotations by "hiding the complexity" of the actual annotation task and employing the "wisdom of the crowds". In this demo paper we present two games with a single purpose: finding regions in images that correspond to given terms. We discuss approach, implementation, and preliminary results of our work and give an outlook to immediate future work.
用人类计算和有目的的游戏寻找图像区域
手动图像标注是一项繁琐且耗时的任务,而自动化方法容易出错且结果有限。人类计算,特别是有目的的游戏,已经显示出通过“隐藏实际注释任务的复杂性”和使用“群体智慧”来创造高质量注释的潜力。在这篇演示论文中,我们展示了两个游戏,它们的目的只有一个:在图像中找到与给定项对应的区域。我们讨论了我们工作的方法、实施和初步结果,并对近期的未来工作进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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