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Automatic labelling of urban point clouds using data fusion
[article]
2021
arXiv
pre-print
In this paper we describe an approach to semi-automatically create a labelled dataset for semantic segmentation of urban street-level point clouds. We use data fusion techniques using public data sources such as elevation data and large-scale topographical maps to automatically label parts of the point cloud, after which only limited human effort is needed to check the results and make amendments where needed. This drastically limits the time needed to create a labelled dataset that is
arXiv:2108.13757v2
fatcat:chalovumgzf5bc2xn6wtw7dtsu