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

Nina Singer, Vijayan K. Asari

2021IEEE Access29 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Benchmark (surveying)Computer scienceSegmentationPreprocessorArtificial intelligenceLidarScale (ratio)Data miningMachine learningCartographyRemote sensingGeographyRemote Sensing and LiDAR Applications3D Surveying and Cultural HeritageRobotics and Sensor-Based Localization
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