通过StreetView影像和付费众包绘制兴趣点
On the mapping of Points of Interest through StreetView imagery and paid crowdsourcing
摘要：
利用志愿人员已成为生成准确地理信息的低成本替代办法，这种办法被称为数字地理信息。然而，VGI受限于要绘制地图的区域中志愿者的数量和可用性，阻碍了大区域的可扩展性，并且难以在时间范围内绘制地图。幸运的是，街景图像的可用性使城市环境的虚拟探索成为可能，使招募不一定位于要绘制地图的地区的贡献者成为可能。在本文中，我们描述的设计，实施和评估的虚拟城市浏览器（VCE），一个系统来收集的坐标点的兴趣在一个有界的区域内的街景服务与使用付费众包。我们的评估表明，付费的众包工作者可以有效地找到POI，并且几乎覆盖了所有区域。关于完整性，我们的方法并不能找到专家或VGI社区发现的所有POI，但能够找到他们没有发现的POI，这表明互补性。我们还研究了将一定数量的工人\emph{taboo}已经发现的PoIs用于新工人的影响，发现它鼓励工人进行更多的探索，增加检测到的PoIs的数量，并降低成本。
英文摘要：
The use of volunteers has emerged as low-cost alternative to generate accurate geographical information, an approach known as Volunteered Geographic Information (VGI). However, VGI is limited by the number and availability of volunteers in the area to be mapped, hindering scalability for large areas and making difficult to map within a time-frame. Fortunately, the availability of street-view imagery enables the virtual exploration of urban environments, making possible the recruitment of contributors not necessarily located in the area to be mapped. In this paper, we describe the design, implementation, and evaluation of the Virtual City Explorer (VCE), a system to collect the coordinates of Points of Interest within a bounded area on top of a street view service with the use of paid crowdworkers. Our evaluation suggests that paid crowdworkers are effective for finding PoIs, and cover almost all the area. With respect to completeness, our approach does not find all PoIs found by experts or VGI communities, but is able to find PoIs that were not found by them, suggesting complementarity. We also studied the impact of making PoIs already discovered by a certain number of workers \emph{taboo} for incoming workers, finding that it encourages more exploration from workers , increase the number of detected PoIs , and reduce costs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
