GENERAL POINT CLOUD FEATURE EXTRACTION AND MATCHING ALGORITHEM

被引：0

作者：

Gao Jingxi ^{[1
]}

Gao Feng ^{[1
]}

Teng Shuhua ^{[1
]}

Zhang Xing ^{[1
]}

Tan Zhiguo ^{[1
]}

Wang Ling ^{[1
]}

机构：

[1] Hunan First Normal Univ, Sch Elect Informat, Changsha 410205, Peoples R China

来源：

2022 19TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP) | 2022年

关键词：

Point cloud feature extraction; Feature matching; Large dynamic; High precision;

D O I：

10.1109/ICCWAMTIP56608.2022.10016493

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

3D scene perception and reconstruction based on laser point cloud is an important research direction in digital city, virtual reality and other fields. The common point cloud matching method generally refers to solving the point cloud correspondence under low dynamic conditions, but it cannot solve the point cloud matching problem under large dynamic conditions. Therefore, this paper proposes a new point cloud feature extraction and matching method, which is compatible with point cloud matching under low dynamic and large dynamic conditions. Experiments show that the proposed algorithm can adaptively solve the point cloud matching problem under various dynamic conditions, and has high accuracy.

引用

页数：6

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