Adaptive Extraction of UAV Photogrammetric Point Cloud Road Surface
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    Abstract:

    In UAV photogrammetry, traditional ground point cloud extraction methods have poor adaptability when extracting roads from image point cloud data. Therefore, this study proposes a UAV photogrammetric point cloud road adaptive extraction method. Firstly, the point cloud is divided into three categories based on its spatial geometric characteristics. Then, corresponding methods are applied to remove non-road point cloud categories. Finally, the point cloud data obtained through the adaptive extraction method is filtered for smoothing and subjected to color-based region growing segmentation. Experimental results show that the I-class error of road point cloud extracted by this method is 4.97%, and the II-class error is 1.14%. This method effectively extracts target road surfaces, improving the efficiency of point cloud data processing in UAV photogrammetric applications.

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李威祥,李武劲,陈思源.无人机摄影测量点云道路自适应提取.计算机系统应用,2024,33(2):232-238

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History
  • Received:July 25,2023
  • Revised:August 24,2023
  • Online: December 25,2023
  • Published: February 05,2023
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