3D Point Cloud Cluster Analysis Based on Principal Component Analysis of Normal-vectors

被引：0

作者：

Hayata, Takeshi ^{[1
]}

Hotta, Tomitaka ^{[2
]}

Iwakiri, Munetoshi ^{[1
]}

机构：

[1] Natl Def Acad Japan, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 2398686, Japan

[2] Japan Maritime Selfdef Force, Tokyo, Japan

来源：

2015 IEEE 4TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE) | 2015年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Technical demands for extraction of significant components from spatial models are increasing as 3D sensors and their application technology has been developed and popularized. In this paper, we propose the 3D point cloud cluster analysis based on the principal component analysis(PCA) of normal-vectors. The distribution of normal vectors depends on a 3D surface shape within the local neighborhood. We discussed the PCA of the distribution of normal vectors to the point cloud. The results of the experiment show that our method could classify a local point cloud as a plane, a boundary and a vertex.

引用

页码：511 / 512

页数：2