论文标题
门：巨石分割的数据集。统计属性和搅拌器设置
DOORS: Dataset fOr bOuldeRs Segmentation. Statistical properties and Blender setup
论文作者
论文摘要
检测小体表面巨石的能力对基于视觉的应用（例如在关键操作和导航过程中的危险检测）有益。由于各种不规则形状，巨石种群的特征以及照明条件的快速变异性，此任务是具有挑战性的。此外，缺乏用于这些应用程序的公开标记的数据集潮湿有关数据驱动算法的研究。在这项工作中，作者提供了一个统计表征和设置，用于生成有关公开可用物体上巨石的两个数据集。
The capability to detect boulders on the surface of small bodies is beneficial for vision-based applications such as hazard detection during critical operations and navigation. This task is challenging due to the wide assortment of irregular shapes, the characteristics of the boulders population, and the rapid variability in the illumination conditions. Moreover, the lack of publicly available labeled datasets for these applications damps the research about data-driven algorithms. In this work, the authors provide a statistical characterization and setup used for the generation of two datasets about boulders on small bodies that are made publicly available.
