DOORS: Dataset fOr bOuldeRs Segmentation. Statistical properties and Blender setup
This addresses a data scarcity problem for researchers in vision-based applications like hazard detection and navigation in space, but it is incremental as it focuses on dataset creation rather than algorithmic advancement.
The authors tackled the lack of labeled datasets for boulder detection on small bodies by providing a statistical characterization and setup for generating two publicly available datasets.
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.