Weighted multiple point cloud fusion

to related objects

Abstract: Multiple viewpoint 3D reconstruction has been used in recent years to create accurate complete scenes and objects used for various applications. This is to overcome limitations of single viewpoint 3D digital imaging such as occlusion within the scene during the reconstruction process. In this paper, we propose a weighted point cloud fusion process using both local and global spatial information of the point clouds to fuse them together. The process aims to minimize duplication and remove noise while maintaining a consistent level of details using spatial information from point clouds to compute a weight to fuse them. The algorithm improves the overall accuracy of the fused point cloud while maintaining a similar degree of coverage comparable with state-of-the-art point cloud fusion algorithms

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Notes: Journal of photogrammetry, remote sensing and geoinformation science. - 93, 1 (2025) , 65-78, ISSN: 2512-2819

Event: Veröffentlichung

(where): Freiburg

(who): Universität

(when): 2024

Creator: Poku-Agyemang, Kwasi Nyarko
Reiterer, Alexander

Contributor: Albert-Ludwigs-Universität Freiburg. Professur für Monitoring von Großstrukturen

DOI: 10.1007/s41064-024-00310-1

URN: urn:nbn:de:bsz:25-freidok-2568628

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:34 AM CEST

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Time of origin

2024

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