Journal of System Simulation ›› 2016, Vol. 28 ›› Issue (9): 2154-2158.

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Point Cloud Modeling Based on Compactly Supported Radial Basis Function under KD Tree Index Strategy

Li Jia1,2,3,4, Duan Ping1, Sheng Yehua2,3,4, Lü Haiyang2,3,4, Zhang Siyang2,3,4   

  1. 1. School of Tourism and Geographical Sciences of Yunnan Normal University, Kunming 650500, China;
    2. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China;
    3. State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China;
    4. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • Received:2015-05-28 Revised:2015-07-30 Online:2016-09-08 Published:2020-08-14

Abstract: Modeling constructed by Compactly Supported Radial Basis Function (CSRBF) and visualization will fail. The main reason is that exhaustive search results in out of memory. KD tree can void exhaustive search due to the advantage of quickly searching. CSRBF combined KD tree was used to construct point cloud model. Modeling approach of CSRBF based on KD tree was proposed. KD tree index of the point cloud was constructed. CSRBF interpolation method was used to construct implicit function model of point cloud. Marching Cubes algorithm was to display model in 3D manner. The experimental results with rabbit point cloud show that it is feasible for point cloud modeling with CSRBF based on KD tree.

Key words: point cloud, modeling, KD tree, compactly supported radial basis function

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