Polygon consensus: smart crowdsourcing for extracting building footprints from historical maps
Polygon consensus: smart crowdsourcing for extracting building footprints from historical maps
复制标题
多边形共识：从历史地图中提取建筑足迹的智能众包
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
M. Arteaga
中科院分区：
文献类型：
--
作者：
Benedikt Budig;Thomas C. van Dijk;F. Feitsch;M. Arteaga
在三年的时间里，纽约公共图书馆运行了一个众包项目，从19世纪和世纪初的保险地图集中提取建筑足迹的多边形表示。正如众包项目中常见的那样，整体问题被分解为小的用户任务，每个任务被分配给多个用户。在多边形代表建筑物足迹的情况下，目前还不清楚如何最好地将答案整合到多数投票中：给定一组表面上描述相同足迹的多边形，共识是什么？我们讨论了理想的属性，这样的“共识多边形”，并得出一个有效的算法。我们已经在对应于200个足迹的大约3，000个多边形上手动评估了该算法，并观察到我们的算法共识多边形对于96%的足迹是正确的，而只有85%的（输入）人群多边形是正确的。
Over the course of three years, the New York Public Library has run a crowdsourcing project to extract polygonal representation of the building footprints from insurance atlases of the 19th and early-20th century. As is common in crowd-sourcing projects, the overall problem was decomposed into small user tasks and each task was given to multiple users. In the case of polygons representing building footprints, it is unclear how best to integrate the answers into a majority vote: given a set of polygons ostensibly describing the same footprint, what is the consensus? We discuss desirable properties of such a "consensus polygon" and arrive at an efficient algorithm. We have manually evaluated the algorithm on approximately 3,000 polygons corresponding to 200 footprints and observe that our algorithmic consensus polygons are correct for 96% of the footprints whereas only 85% of the (input) crowd polygons are correct.