Paper
3 June 2024 Research on target center elevation extraction method based on photogrammetric point cloud
Jianliang Zhang, Tong Shi, Zhichong Zhao, Ruan Qin, Jiajia Yuan
Author Affiliations +
Abstract
Aiming at the problem that it is difficult to obtain the elevation of the target in the point cloud data of inclined photogrammetry, an automatic extraction method of the elevation of the center point of the target based on the K-Means clustering algorithm and the minimum root-mean-square error is proposed. Firstly, the point cloud of the target area is determined based on the known plane coordinates and divided into elevation intervals, and the elevation intervals are rejected according to different thresholds to achieve the denoising effect; secondly, the ground point cloud and target point cloud are distinguished based on the K-Means clustering algorithm; and finally, the elevation of target center point is determined by the minimum root mean square error from the target point cloud to the center point elevation. The point cloud data generated by UAV photogrammetry is used to carry out several experiments on the method of this paper, and the experimental results show that this algorithm can realize the rapid and automatic extraction of the elevation of the center point of the target, and the difference between the results and the manual extraction is better than 2cm, and it has a certain role in improving the recognition accuracy and work efficiency.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jianliang Zhang, Tong Shi, Zhichong Zhao, Ruan Qin, and Jiajia Yuan "Research on target center elevation extraction method based on photogrammetric point cloud", Proc. SPIE 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 131700U (3 June 2024); https://doi.org/10.1117/12.3032169
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KEYWORDS
Point clouds

Detection and tracking algorithms

Denoising

Target acquisition

Photogrammetry

3D modeling

Data modeling

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