KEYWORDS: Point clouds, Data modeling, 3D modeling, Modeling, Reconstruction algorithms, Tunable filters, LIDAR, Systems modeling, Education and training, Process modeling
In order to explore a new way of quick dressing of the ski jump in the ski training ground and solve the problems of low modeling accuracy and poor dressing accuracy of the ski jump; This paper proposes an improved 3D point cloud segmentation method for diving platform surface modeling. This method improves the traditional RANSAC algorithm by selecting distance threshold adaptively. The new method is compared with the traditional method. The results show that the running time and the number of iterations of the new method are significantly reduced compared with the traditional method in the process of point cloud segmentation on different data sets, and the effect of point cloud segmentation and extraction of the collected jump point cloud data is better. This paper first proposed a automation platform surface modeling and trim architecture, solve the snow surface for subsequent provides a precise modeling and repair solution.
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