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

Authors

Li Jia, 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;
Duan Ping, 1. School of Tourism and Geographical Sciences of Yunnan Normal University, Kunming 650500, China;;
Yehua Sheng, 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;
Haiyang Lü, 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;
Siyang Zhang, 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;

Abstract

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.

Recommended Citation

Jia, Li; Ping, Duan; Sheng, Yehua; Lü, Haiyang; and Zhang, Siyang (2020) "Point Cloud Modeling Based on Compactly Supported Radial Basis Function under KD Tree Index Strategy," Journal of System Simulation: Vol. 28: Iss. 9, Article 34.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss9/34

First Page

2154

Revised Date

2015-07-30

DOI Link

https://doi.org/

Last Page

2158

CLC

TP391.41

Recommended Citation

Li Jia, Duan Ping, Sheng Yehua, Lü Haiyang, Zhang Siyang. Point Cloud Modeling Based on Compactly Supported Radial Basis Function under KD Tree Index Strategy[J]. Journal of System Simulation, 2016, 28(9): 2154-2158.