根据点云序列重建三维场景的全局细化算法

IF 0.4 4区计算机科学 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC

Journal of Communications Technology and Electronics Pub Date : 2023-12-01 DOI:10.1134/s1064226923120124

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引用次数: 0

摘要

摘要--点云注册是许多计算机视觉问题的核心问题。然而，当存在多个点云时，要确保点云配对注册结果的全局一致性仍是一个挑战，因为不同的扫描应转换到一个共同的坐标系。本文介绍了一种全局细化算法，该算法首先估算旋转，然后估算平行平移。对于旋转的全局细化，采用了基于矩阵的闭式算法。对于平行平移的全局细化，也采用了闭式算法。将所提出的算法与其他全局细化算法进行了比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Global Refinement Algorithm for 3D Scene Reconstruction from a Sequence of Point Clouds

Abstract—Point cloud registration is a central problem in many computer vision problems. However, ensuring global consistency of the results of pairwise registration of point clouds is still a challenge when there are multiple clouds because different scans should be converted to a common coordinate system. This paper describes a global refinement algorithm that first estimates rotations and then estimates parallel translations. For global refinement of rotations, a closed-form algorithm based on matrices is used. For global refinement of parallel translations, a closed-form algorithm is also used. The proposed algorithm is compared with other global refinement algorithms.

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来源期刊

Journal of Communications Technology and Electronics 工程技术-电信学

CiteScore

1.00

自引率

20.00%

发文量

170

审稿时长

10.5 months

期刊介绍： Journal of Communications Technology and Electronics is a journal that publishes articles on a broad spectrum of theoretical, fundamental, and applied issues of radio engineering, communication, and electron physics. It publishes original articles from the leading scientific and research centers. The journal covers all essential branches of electromagnetics, wave propagation theory, signal processing, transmission lines, telecommunications, physics of semiconductors, and physical processes in electron devices, as well as applications in biology, medicine, microelectronics, nanoelectronics, electron and ion emission, etc.