DALES Objects: A Large Scale Benchmark Dataset for Instance Segmentation in Aerial Lidar
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...
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| Veröffentlicht in: | IEEE access 2021, Vol.9, p.97495-97504 |
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| creator | Singer, Nina M. Asari, Vijayan K. |
| description | 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. |
| doi_str_mv | 10.1109/ACCESS.2021.3094127 |
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| source | IEEE Open Access Journals; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | 3D data set aerial vision airborne system ALS benchmark data Benchmark testing Benchmarks data annotation Data collection Datasets Deep learning earth scan Image annotation Instance segmentation Labels Laser radar laser scan Lidar point cloud semantic segmentation Semantics Task analysis Three-dimensional displays Vegetation mapping |
| title | DALES Objects: A Large Scale Benchmark Dataset for Instance Segmentation in Aerial Lidar |
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