DALES Objects: A Large Scale Benchmark Dataset for Instance Segmentation in Aerial Lidar

Autor: Nina M. Singer, Vijayan K. Asari
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IEEE Access, Vol 9, Pp 97495-97504 (2021)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2021.3094127
Popis: We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.
Databáze: Directory of Open Access Journals