首页|基于改进特征点匹配的三维点云数据配准算法应用探究

基于改进特征点匹配的三维点云数据配准算法应用探究

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三维点云配准算法作为计算机辅助制造工程的重要构成,在三维重建、目标物形状检测等领域有着重要的应用.为了实现目标物体的完整测量,一方面需要从点云数据中获取精确的特征点集,另一方面需要压制噪声信息.基于特征点匹配的三维点云配准算法简化了特征提取的复杂度,提升了配准的精度和速度,能够实现目标物体的高效配准.本文就基于改进特征点匹配的三维点云数据配准算法应用展开探究.
Application of 3D Point Cloud Data Registration Algorithm Based on Improved Feature Point Matching
As an important component of computer-aided manufacturing engineering,3D point cloud registration algorithm has important applications in the fields of 3D reconstruction and target object shape detection.In order to achieve a complete measurement of the target object,it is necessary to obtain an accurate set of feature points from the point cloud data,and suppress the noise information.The 3D point cloud registration algorithm based on feature point matching simplifies the complexity of feature extraction,improves the accuracy and speed of registration,and can achieve efficient registration of target objects.This paper explores the application of 3D point cloud data registration algorithm based on improved feature point matching.

point cloud registrationfeature point matchingpoint feature histogramfeature description

吴辰、欧宇钧、朱沫

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中海油能源发展装备技术有限公司深圳分公司 广东 深圳 518054

点云配准 特征点匹配 点特征直方图 特征描述

2024

科学与信息化

科学与信息化

ISSN:
年,卷(期):2024.(2)
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