Point Cloud Reconstruction Based on SVR

被引：0

作者：

Sun, Jin-guang ^{[1
]}

Wang, Jun-tao ^{[1
]}

Yang, Xin-nian ^{[1
]}

Li, Yang ^{[1
]}

机构：

[1] Liaoning Tech Univ, Sch Elect & Informat Engn, Huludao Liaoning 125105, Peoples R China

来源：

MEMS, NANO AND SMART SYSTEMS, PTS 1-6 | 2012年 / 403-408卷

关键词：

Point Cloud Reconstruction; Surface fitting; SVR; PSO;

D O I：

10.4028/www.scientific.net/AMR.403-408.3267

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a point cloud reconstruction algorithm which based on SVR(support vector regression). Firstly, the point cloud data pre-processing, filter out noise points. Then train the point by SVR, and we can get the function of surface expression. Finally, using the Marching Cube algorithm to visualize the implicit function. Experimental results show that the algorithm is more robust and more efficient.

引用

页码：3267 / 3270

页数：4

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