期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2020
卷号：V-4-2020
页码：49-56
DOI：10.5194/isprs-annals-V-4-2020-49-2020
语种：English
出版社：Copernicus Publications
摘要：The term "Crowdsourcing" goes back to Jeff Howe (Howe, 2006) and represents a neologism of the words "crowd" and "outsourcing". Unlike outsourcing, where companies outsource certain tasks to known third parties, crowdsourcing outsources tasks to unknown workers (crowdworkers) on the Internet. This allows companies to access large numbers of workers who would otherwise not be available. In this paper, we will discuss an approach for the crowd-based collection of trees by means of minimum bounding cylinders from 3D point clouds. We will demonstrate the used web-interface and compare the results with reference data. To improve the quality of the results, we collect the data not only once but multiple times. This enables us to implement a so-called “Wisdom of the Crowd” approach where we can identify automatically outliers and derive integrated cylinders. We will show in this paper that this approach increases significantly the quality of the results.
