3D HIGH-EFFICIENCY AND HIGH-PRECISION MODEL-DRIVEN MODELLING FOR POWER TRANSMISSION TOWER
Constructing the transmission tower from LiDAR point clouds is a fundamental step for smart grid. However, currently the transmission tower construction method relies heavily on manual editing, which is far from the practical industrial application. This paper proposes a model-driven based method to...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-11-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIV-4-W3-2020/421/2020/isprs-archives-XLIV-4-W3-2020-421-2020.pdf |
| Summary: | Constructing the transmission tower from LiDAR point clouds is a fundamental step for smart grid. However, currently the transmission tower construction method relies heavily on manual editing, which is far from the practical industrial application. This paper proposes a model-driven based method to realize 3D construction of transmission tower fast and accurately. This method first generates different types of 3D tower models. Then, it calculates the direction characteristic of point clouds distribution using the obtained transmission towers point clouds. While finding the principal direction of transmission towers, the local coordinates of the transmission towers are settled. And then the key points are captured in a semi-automatically way. According to these key points, the transmission tower model that best matches the point clouds is selected using the model matching algorithm. Comparing with the existing traditional manual editing methods, the method proposed in this paper can ensure the integrity and accuracy of the reconstructed tower model using the model-driven based strategy. The proposed method makes a trade-off between manual editing and efficiency, which guarantees the quality of tower modelling. And the feasibility and practicability of the proposed method are verified by the experiments on real-world point clouds data. |
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| ISSN: | 1682-1750 2194-9034 |